ISPIRE, GMES and GEOSS Activities, Methods and Tools towards a Single Information Space in Europe for the Environment

I�SPIRE, GMES and GEOSS Activities, Methods

and Tools towards a Single Information Space

in Europe for the Environment

Dr. Karel Charvat • Dr. Maris Alberts • Sarka Horakova

Editors

Tehnoloģiju attīstības forums Wirelessinfo

Riga 2009

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UDK 62:001(082) In 660

Editors:

Dr. Karel Charvat Wirelessinfo Cholinska 19, 784 01 Litovel, Czech Republic [email protected]

Dr. Maris Alberts Institute of Mathematics and Computer Science, University of Latvia 29 Rainis blvd., Riga LV - 1459, Latvia [email protected]

Sarka Horakova Wirelessinfo Cholinska 19, 784 01 Litovel, Czech Republic [email protected]

Reviewers:

Prof. Juris Miklesons University of Latvia, Faculty of Computing 19 Rainis blvd., Riga, Latvia [email protected]

Dr. Zuzana Boukalova Regional Environmental Center Senovazna 2, 110 00 Prague, Czech Republic [email protected]

Publishers:

Tehnoloģiju attīstības forums Wirelessinfo Kr.Barona iela 32-7 Cholinska 19 Rīga, LV 1011 Litovel, 784 01 Latvia 2009 Czech Republic 2009 www.tdf.lv www.wirelessinfo.cz

This book has been published within the EarthLookCZ project (OK488) supported by the Ministry of Education, Youth and Sports within the frame of OK – EUPRO Programme. All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher.

ISB� 978-9934-8105-1-0

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Preface

The book “INSPIRE, GMES and GEOSS Activities, Methods and Tools towards a Single Information Space in Europe for the Environment” was prepared by EarthLookCZ (project EUPRO OK488) in cooperation with Tehnoloģiju attīstības forums, Latvia. The contents of the book are based not only on the results of the EarthLookCZ project, but also on the results of the following ones:

• Plan4all (eContentplus project)

• Humboldt (6.FP project 030962)

• SOSI CZ ( ESA project)

• enviroGRIDS (7.FP project 226740)

• GE�ESI-DR (7.FP project 212073)

• WI�SOC (6.FP project 033914)

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Content

INTRODUCTION Karel Charvat, Maris Alberts 6

PLAN4ALL - INTEROPERABILITY OF SPATIAL PLANNING INFORMATION IN THE CONTEXT OF THE INFRASTRUCTURE FOR SPATIAL INFORMATION IN THE EUROPEAN COMMUNITY – INSPIRE Tomas Mildorf 11

GMES NEEDS DESCRIBED SPATIAL DATA Otakar Cerba 23

GMES – THE EUROPEAN AMBITION TO BRING EARTH OBSERVATION CAPACITIES IN DAILY USE Ondrej Mirovsky 30

SPATIAL OBSERVATION SERVICES AND INFRASTRUCTURE IN THE CZECH REPUBLIC – SOSI CZ Lukas Brodsky, Milan 3ovacek, Jan Kolomaznik, Vaclav Vobora, Lubos Kucera

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THE BLACK SEA CATCHMENT OBSERVATION SYSTEM BUILT ON A GRID-ENABLED SPATIAL DATA INFRASTRUCTURE Anthony Lehmann, Gregory Giuliani, 3icolas Ray, Karin Allenbach, Karel

Charvat, Dorian Gorgan, Mamuka Gvilava, Tamar Bakuradze, Seval Sozen,

Cigdem Goksel and the enviroGRIDS consortium 42

EMERGING INFRASTRUCTURES FOR MANAGING EARTH SCIENCE DATA: EXPERIENCE AT ESA Roberto Cossu and Luigi Fusco 59

A NOVEL APPROACH TO ENVIRONMENTAL MONITORING SYSTEM FOR LANDSLIDES AND FIRE DETECTION Paolo Capodieci and Fabio Mengoni 84

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EARTHLOOKCZ - GMES DATA PUBLICATION, COMBINATION AND SHARING ON THE WEB Petr Horak, Sarka Horakova, Karel Charvat, Martin Vlk 102

USING GEOHOSTING PRINCIPLES FOR PUBLICATION OF USERS’ GMES DATA WITHIN THE EARTHLOOKCZ PROJECT Petr Horak, Sarka Horakova, Karel Charvat, Martin Vlk 110

GEOPORTAL FOR EVERYONE Premysl Vohnout, Jachym Cepicky, Stepan Kafka 133

SENSORS AND ANALYSIS IN WEB ENVIRONMENT Karel Charvat, Jan Jezek, Jachym Cepicky 140

MONITORING OF AIR POLLUTION DAMAGE TO FOREST Vladimir Henzlik, Josef Fryml 148

CONCLUSION Karel Charvat 167

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Introduction

Karel Charvat1, Maris Alberts2

1 Wirelessinfo, Cholinska 1048/19, 784 01 Litovel, Czech Republic, [email protected]

2Institute of Mathematics and Computer Science, University of Latvia; Raina bulvaris 29, Riga, LV-1459, Latvia, [email protected]

Abstract: The paper explains the purpose of the publication which is to describe how INSPIRE, GMES and GEOSS could be integrated into Single European Information Space. The paper deals with the main task of INSPIRE, GMES and GEOSS and also with tools which could integrate all the three initiatives. The document gives an overview of single contributions in the book and how they explain the roles of single initiatives and their integration into the vision. The paper also explains the role of Earthlook technologies in the concept of integration of INSPIRE, GEOSS and GMESS into SISE.

Keywords: GMES, GEOSS, GMES, SEIS, SISE.

1 Single Information Space in Europe for the Environment

In 2005 European Commission launched the i2010 strategy: A European Information Society for Growth and Employment. The Commission defines three pillars for i2010 [1]:

• Single European Information Space

• Innovation and Investment

• Inclusive European Information Society

The Objectives of Single European Information Space are to offer high-bandwidth communications, rich content and digital services with a market-oriented regulatory framework.

The concept of Single Information Space in Europe for the Environment (SISE) was also for the first time formulated in 2005. The basic idea is that the environmental institutions, service providers and citizens can collaborate or use available information without technical restraints [2]. The following scheme defines the relation of SISE and other ongoing European initiatives.

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Shared Environmental Information Systems – Peeling the Onion [3]

The final vision of SISE was defined by the workshop of European experts in February 2008 [4]. The main objectives of SISE are as follows:

SISE Context

• Complexity Management

• Environmental Legislation in Europe

Application/Services

• SISE Services

• Process Chaining & Uncertainties

• Real-time Mapping & Modelling

• Thesauri

• Open Standards & Open Source Software

SISE Open Semantics & Standards

• Standardisation & Framework Projects

• Standardisation & Community Knowledge

• Semantic Web Technologies for the SISE

• Ontologies

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Data Interoperability &Web Communities

• Web 2.0 Technologies

• Data Provision in the Semantic Web

• SOA/Web Services & Model Driven Communities

• Social SISE

Data Visualisation & Modelling including Risk Assessment

• Visualisation of Environmental Data

• SOA & Semantic Web Services

• Simulation & Modelling

• Complex 3D/4D Models

• Chained Web Services & Legacy Systems

SISE Deployment Models

• From Framework Projects to Market Deployment

• Project’s Knowledge Loss

• Regional Application of European Interoperability Standards

• SISE & Business Models

• Environmental Information Service Economy (EISE)

2 SEIS, I�SPIRE, GMES and GEOSS

Shared Environmental Information System (SEIS) will be based on a set of principles [5]:

• Managing all environmental information as closely as possible to its source

• Collecting environmental information once, and sharing it with others

• Making environmental information available to public authorities

• Making environmental information readily accessible to end-users to enable them to assess the state of the environment in a timely fashion

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• Making environmental information accessible to enable comparisons at the appropriate geographical scale

• Making environmental information fully available to general public

INSPIRE is a Directive 2007/2/EC of the European Parliament and of the Council of 14 March 2007 establishing the Infrastructure for Spatial Information in the European Community[6]. INSPIRE addresses mainly such policy and activities that may have direct or indirect impact on environment; there are also implications and overlaps with other activities, policies and initiatives with complementary objectives. The Directive applies to spatial data and services held by or on behalf of public authorities and used in the performance of their public tasks. The Directive does not require collecting of new spatial data; it foresees that data should be collected only once and then stored, made available and maintained at the most appropriate level; the infrastructure should ensure the possibility of combining data from different sources in a consistent way and sharing them among users and applications.

The vision for Global Earth Observation System of Systems (GEOSS) is to “realize that the originators of future decisions and activities for the benefit of humankind are well informed thanks to coordinated, comprehensive and sustained Earth observations” [7]. GEOSS must provide access and improved interoperability both for the existing and future observation systems. GEOSS is based on voluntary contribution of governments and international organizations.

GMES (Global Monitoring for Environment and Security) is the European Initiative for the establishment of European Capacity for Earth Observation. The main objective of GMES is to monitor and better understand our environment. GMES provides decision-makers who rely on strategic information with regard to environmental and security issues with an independent and permanent access to reliable data [8].

Roles of single contributions

Tomas Mildorf in his contribution PLA34ALL - Interoperability of Spatial

Planning Information in the Context of the Infrastructure for Spatial Information

in the European Community – I3SPIRE demonstrates the implementation of INSPIRE principles in the area of spatial planning. In the contribution by Ota Cerba GMES 3eeds Described Spatial Data the same case is used to demonstrate how principles of INSPIRE have to be implemented for GMES. Ondrej Mirovsky (GMES – The European Ambition to Bring Earth Observation Capacities into

Daily Use) explains basic principles of GMES. The objective of Lukas Brodsky et al. (Spatial Observation Services and Infrastructure in the Czech Republic – SOSI

CZ) demonstrates how GMES activity could be integrated into SEIS. Anthony

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Lehmann et al. (The Black Sea Catchment Observation System built on a Grid-

Enabled Spatial Data Infrastructure) show the advantage of using GRID technology in the frame of SDI and GEOSS. Roberto Cossu and Luigi Fusco (Emerging Infrastructures for Managing Earth Science Data: Experience at ESA) demonstrate on the base of ESA experience the advantage of GRID technologies for GMES. New sensor technology and new approach of sensor monitoring are presented by Paolo Capodieci and Fabio Mengoni (A 3ovel Approach to

Environmental Monitoring System for Landslides and Fire detection).

The next four chapters are dedicated to the Earthlook project. Petr Horak et al. (EarthLookCZ - GMES data publication, combination and sharing on the web) explain basic principles of integration of GMES and INSPIRE principles into the Earthlook project. In Petr Horak et al. (Using Geohosting Principles for

Publication of Users’ GMES Data within the EarthLookCZ Project) the idea of Geohosting as the method of public particpation on SDI building is presented. Premysl Vohnout et al. (Geoportal for Everyone) then describes innovative solution of GeoPortal, which is a basic component for Earthlook data discovery and visualisation. The last presentation by Karel Charvat et al. (Sensors and analysis in Web Environment) describes Earthlook technologies for in situ monitoring and analysis. The last part of the book by Vladimir Henzlik and Josef Fryml (Monitoring of Air Pollution Damage to Forest} descibes one of the Czech information sources for GMES and GEOSS.

References

1. COMMUNICATION FROM THE COMMISSION TO THE COUNCIL, THE EUROPEAN PARLIAMENT, THE EUROPEAN ECONOMIC AND SOCIAL COMMITTEE AND THE COMMITTEE OF THE REGIONS “i2010 – A European Information Society for growth and employment” {SEC(2005) 717} Brussels, 1.6.2005 COM(2005) 229 final

2. http://ict-ensure.tugraz.at/en/index.php/ensure/Content2/SISE 3. Thomas Pick, Reinhard Schmalz, Fred Kruse, Martin Klenke Information for the

People: PortalU, an environmental information service for the communal level in Lower Saxony, http://www.epma.cz/Docs/EEEGD08/Pick.pdf

4. John J O’Flaherty WP Session on Objective ICT-2009.6.4: ICT for environmental services and climate change adaptation, Brussels 27 Nov 2008

5. J. Hřebíček and W. Pillmann Shared Environmental Information System and Single Information Space in Europe for the Environment: Antipodes or Associates? European conference of the Czech Presidency of the Council of the EU TOWARDS eENVIRONMENT,

6. ECP-2008-GEO-318007, Plan4all, INSPIRE Requirements Analysis 7. Eva Klien, Alessandro Annoni, Pier Giorgio Marchetti The GIGAS project – an

action in support to GEOSS, INSPIRE, and GMES, European conference of the Czech Presidency of the Council of the EU TOWARDS eENVIRONMENT,

8. http://www.gmes.info/

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PLA�4ALL - Interoperability of Spatial Planning

Information in the Context of the Infrastructure for Spatial

Information in the European Community – I�SPIRE

Tomas Mildorf

University of West Bohemia in Pilsen, Faculty of Applied Sciences, Department of mathematics, Section of Geomatics, Univerzitni 22, Pilsen, 306 14, Czech Republic

[email protected]

Abstract. Spatial planning has a crucial role in the context of social, political, economic and environmental issues. There is a big diversity in data collection, storing, processing and provision. The legal situation incorporates similar problems. The heterogeneity in spatial planning limits its use in decision-making in transboundary context, including impact assessment and evaluation of plans. Infrastructure for Spatial Information in the European Community (INSPIRE) can significantly contribute to support spatial planning processes by increasing transparency and developing shared methodologies.

Keywords: Spatial planning, Harmonisation, Interoperability, INSPIRE, Infrastructure for spatial information

1 Introduction

Human activity is a term that is very often declined in conjunction with social, political, economic and environmental issues. Spatial planning is one of the most important areas that strongly influence these issues on all levels. Sustainable planning addresses the environment where people live and work, the location of social and economic activities, the way in which the resources we possess are exploited, etc. Spatial planning acts in bottom-up and top-down directions between all levels of government. National, regional and local authorities face important challenges in the development of territorial frameworks and concepts every day.

The situation is complicated by the diversity and overall complexity of spatial planning. Spatial planning is a holistic activity. All the tasks and processes must be solved comprehensively with input from many various sources. Several authorities are in charge of single spatially relevant topics (e.g. water management, transport, cadastre, geology, etc.). There is a big diversity in data collection, storing, processing and provision. To combine these sources, to perform an analysis and to ensure valuable results are big challenges in spatial

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planning, especially when talking about digital data. We cannot make any high-quality results without taking all the inputs into account. It is necessary to make the inputs interoperable and therefore comparable. This will allow the user to search the data and services, view them, download them and use them with help of IT technologies.

The definitions of spatial planning and related terms are described in section 2. Section 3 focuses on the building of the infrastructure for spatial information in Europe (INSPIRE) [4] and its requirements. Section 4 combines spatial planning and the INSPIRE initiative with a focus on the similarities between them. Heterogeneity in spatial planning is addressed in section 5. This chapter is concluded by challenges for spatial planning in section 6. The main sources of information are the European eContentplus project Plan4all [3] and the INSPIRE initiative [4].

2 Spatial Planning

Terms and their definitions play a crucial role in all activities where cooperation between several sectors is essential. Spatial planning is an example of such cooperation. Terms like spatial planning, land use planning, regional planning and urban planning are often used interchangeably depending on the country. Moreover they do not always have the same meaning between users. Their definitions might be disjointed even within one country. In Europe the preferred term covering all the above mentioned terms is increasingly spatial planning or territorial cohesion. Several concepts are therefore defined in this section.

2.1 Spatial Planning – Territorial Cohesion

Spatial planning refers to the methods used by the public sector to influence the distribution of people and activities in spaces of various scales.

There are several definitions of spatial planning. One of them is mentioned in the European Regional/Spatial Planning Charter (1983) that was adopted by the European Conference of Ministers responsible for Regional Planning (CEMAT). This definition is wide enough to cover the complexity of spatial planning.

Regional/spatial planning gives geographical expression to the economic, social,

cultural and ecological policies of society. It is at the same time a scientific

discipline, an administrative technique and a policy developed as an

interdisciplinary and comprehensive approach directed towards a balanced

regional development and the physical organisation of space according to an

overall strategy.

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At the European level, the term territorial cohesion is also becoming more widely used. It is mentioned in the Lisbon Treaty, in the Green Paper on Territorial Cohesion [11], where the following sentence describing this term is stated, and other documents and initiatives.

Territorial cohesion is about ensuring the harmonious development of all diverse

territories and about making sure that their citizens are able to make the most of

inherent features of these territories. As such, it is a means of transforming

diversity into an asset that contributes to sustainable development of the entire

EU. [11]

2.2 Regional Planning

Regional planning is a branch of land use planning dealing with the organisation

of infrastructure, settlement growth and non-built areas at the scale of a region.

Regional planning generally contributes to regional development, but may also

fulfil additional objectives, such as sustainability in the environmental sense.

Regional planning is generally understood as the spatial planning activities at

regional scale. [12]

2.3 Urban, City and Town Planning

Urban, city or town planning is the planning discipline dealing with the physical,

social, economic and environmental development of metropolitan regions,

municipalities and neighbourhoods. The expression of urban planning consists in

elaborating land-use and building plans as well as local building and

environmental regulations.

3ote: Historically (nineteenth century) urban planning was influenced by the

newly formalised disciplines of architecture and civil engineering which began to

codify both rational and stylistic approaches to solving city problems through

physical design. During the twentieth century, the domain of urban planning was

expanded to include economic development planning, community social planning

and environmental planning. [12]

2.4. Land Use Planning

Land use planning is a branch of public policy which encompasses various

disciplines seeking to order and regulate the use of land in an efficient way. It

means the scientific, aesthetic and orderly disposition of land, resources, facilities

and services with a view to securing the physical, economic, social and

environmental efficiency, health and well-being of urban and rural communities.

[12]

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2.5 Interoperability and Harmonisation

Interoperability and harmonisation - two terms that are essential for the integration of spatial planning information.

Interoperability means the possibility for spatial data sets to be combined, and for

services to interact, without repetitive manual intervention, in such a way that the

result is coherent and the added value of the data sets and services is enhanced.

[4]

Data harmonisation - providing access to spatial data through network services

in a representation that allows for combining it with other harmonised data in a

coherent way by using a common set of data product specifications. [9]

In other words, interoperability means that each country maintains their own infrastructure but adopts a framework that enables existing datasets to be linked up from one country to another. Interoperability may be achieved by either changing (harmonising) and storing existing data sets or transforming them via services for publication in the INSPIRE infrastructure.

Harmonisation means that all countries use a common set of coordinate reference systems, data models, classification systems, etc. Harmonised data help to get better consistency and comparability of data across information systems. Consistency can be achieved through the deletion of redundant or conflicting data. The harmonization process makes information available for the integration of data systems and improves meaning and format across different systems. This result can be obtained by means of a data mapping process that compares the meanings and formats of involved data elements belonging to a specific area (for example GIS information). The harmonisation process therefore applies transformation rules and definitions to the existing heterogeneous data elements in order to have a common representation of the same elements with an improved quality and consistency [10].

3 I�SPIRE

This section describes what is the INSPIRE and what are its principles and requirements. The main source of information are INSPIRE documents [13].

Infrastructure for Spatial Information in the European Community (hereinafter referred to as INSPIRE) was established by the Directive 2007/2/EC of the European Parliament and of the Council of 14th March 2007 (hereinafter referred to as INSPIRE Directive) [4]. INSPIRE lays down general rules to establish an infrastructure for spatial information in Europe for the purposes of Community environmental policies, and policies or activities which may have an impact on the

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environment. The most significant general rules are summarised in the following INSPIRE principles:

• The infrastructures for spatial information in the Member States should be designed to ensure that spatial data are stored, made available and maintained at the most appropriate level;

• It is possible to combine spatial data from different sources across the Community in a consistent way and share them between several users and applications;

• It is possible for spatial data collected at one level of public authority to be shared between all the different levels of public authorities;

• Spatial data are made available under conditions that do not restrict their extensive use;

• It is easy to discover available spatial data, to evaluate their fitness for purpose and to know the conditions applicable to their use.

Infrastructure for spatial information means metadata, spatial data sets and

spatial data services; network services and technologies; agreements on sharing,

access and use; and coordination and monitoring mechanisms, processes and

procedures, established, operated or made available in accordance with the

I3SPIRE Directive. [4]

INSPIRE should be based on the infrastructures for spatial information that are created by the Member States. To ensure that the infrastructures are compatible and usable in a Community and transboundary context, the INSPIRE Directive requires that common Implementing Rules are adopted in a number of specific areas.

INSPIRE addresses mainly policy and activities that may have a direct or indirect impact on the environment. The INSPIRE Directive applies to spatial data sets and services held by or on behalf of public authorities and used in the performance of their public tasks. Data must be in electronic format and must relate to one or more of the themes listed in Annexes I, II or III of the INSPIRE Directive.

The development and implementation of INSPIRE follows a programme of work consisting of three phases. These are the Preparatory (2005-2006), the Transposition (2007-2009) and the Implementation (2009-2019) phases.

The Preparatory Phase (2005-2006) started with the Commission’s proposal for INSPIRE and was successfully finished with its entry into force. The Implementing Rules begun to be drafted with involvement of key stakeholders.

During the Transposition Phase (2007-2009) Member States focused on transposing the INSPIRE Directive's requirements into their own legislative systems. Member States are therefore engaged in implementing the technologies, policies and institutional arrangements that will form the basis for their INSPIRE

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compliant systems. The development of the draft Implementing Rules continued in this phase.

The Implementation Phase (2009-2019) should cover the implementation of the Implementing Rules by Member States and monitoring of the implementation through reporting according to the road map of the INSPIRE.

The Implementing Rules are for the following INSPIRE elements:

• Metadata – INSPIRE metadata profiles for spatial datasets, spatial datasets series and for services are outlined through set of metadata elements. It includes the minimum set of metadata elements necessary to comply with the INSPIRE Directive. It should ensure that all geospatial information resources and data produced and made available by Member States and their constituent organisations are catalogued in a standard way to support a consistent means of discovery, understanding and access across the Community.

• Data Specifications – Data Specifications pertain to the content of a basic set of data themes that each Member State is required to maintain and also the technological standards for communication of those data themes for use. The set of spatial data themes is listed in Annexes I, II and III to the INSPIRE Directive. These rules will enable full data use and interoperability across the INSPIRE network.

• �etwork Services – Member States are required to establish and operate a network of services for the spatial data sets and services. In order to ensure the compatibility and usability of such services on the Community level, it is necessary to lay down the technical specifications and minimum performance criteria for those services with regard to the themes listed in Annexes I, II and III to the INSPIRE Directive. In order to ensure that public authorities and the third parties are given the technical possibility to link their spatial data sets and services to the Network Services, it is necessary to lay down the appropriate requirements for those services (including services that enable discovery, viewing, downloading and data transformation).

• Data and Service Sharing - The INSPIRE Directive requires the development of implementing rules to regulate the provision of access to spatial data sets and services from Member States to the institutions and bodies of the Community.

• Monitoring and Reporting - In order to have a solid basis for decision making related to the implementation of the INSPIRE Directive and to the future evolution of INSPIRE, continuous monitoring of the implementation of the Directive and regular reporting are taking place. Quantitative indicators for assessing the progress of SDI implementation

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in the EU Member States and the structure of qualitative reports are outlined.

4 I�SPIRE & Spatial Planning

INSPIRE is fundamental to support the Community policies, including environmental policy, and to fulfil environmental protection requirements. It is necessary to establish coordination in order to combine high quality information and knowledge from different sectors on different levels (administrative, cultural, etc.) and to underpin policy-making in an integrated way. This is important to help in understanding the complexity and interactions between human activities and environmental impacts. Spatial planning as a holistic activity of public administration, matches the Communities policies that are the core of the INSPIRE initiative. Spatial planning is not directly addressed by INSPIRE, but indirectly, in a complex way through its technical documents.

There are many similarities between the character of spatial planning and the INSPIRE initiative:

• The innovative aspects of INSPIRE include the cooperation of different actors within the involvement of both public and private sector. The spatial planning continuously sees the involvement of different stakeholders (public, private, citizens, associations, etc.).

• The INSPIRE Directive does not require collection of new spatial data. Spatial planning generally utilises data already produced and is not in charge of producing new reference data.

• The main objective of INSPIRE is to establish a European Spatial Data Infrastructure (SDI). Existing Spatial Data Infrastructures are valuable means to support spatial planning processes, especially in transboundary contexts, to enhance exchange of strategic data, to improve the use of impact assessment and evaluation of plans and provisions in spatial planning, with transparency and shared methodology.

• The devolution applied by each Member State to the sub-national planning creates different situations in each country. Measures provided by INSPIRE aim to overcome the differences that may limit the coherence of Spatial Data Infrastructures.

• Almost all the spatial data themes listed in the INSPIRE Annexes, for their general character, are valuable for spatial planning.

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5 Heterogeneity in Spatial Planning

The heterogeneity in spatial planning is well known. A planner from one region has difficulties to combine data from neighbouring region and vice versa. Current spatial planning laws are disjointed and even experts from one country might have difficulties to understand the planning regulations of a neighbouring country. For investors and decision makers it is almost impossible to compare planning regulations across Europe.

The preliminary results from the Plan4all project show the heterogeneity in Europe in terms of spatial planning systems, spatial data infrastructures, terminology, processes in spatial planning, data formats, quality and quantity of content, standards, data models, data availability, user requirements and other aspects [5,6,7,8]. An example is shown by the heterogeneity of levels and instruments of the spatial planning system in the Czech Republic – CR (Fig. 1) and France (Fig. 2). The figures describe the different functional levels in comparison with the administrative levels.

The differences in spatial planning between various administrative units and between different levels of government will remain. Therefore it is not feasible to eliminate the heterogeneity by the harmonisation on local level over entire Europe. Harmonisation on the European level is one of the approaches to make spatial planning interoperable across Europe.

6 Challenges for Spatial Planning

A sustainable resource management (with direct and indirect impact on the environment) improves coordination of spatial development and urban planning as well as investments. An integrated strategy of the European Community policy-making can only be achieved by the establishment of an infrastructure for spatial information (INSPIRE Directive). By using this instrument, and through land use management with Spatial Data Information, municipalities, regions and nations can benefit from the ongoing regional competition to overcome their lack of attractiveness and gain competitive territories. Therefore, the INSPIRE Directive and the use of Spatial Data Infrastructure relates directly to spatial planning and helps for better decisions in policy making.

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Fig. 1. Structogram of the levels and instruments of the spatial planning system in the CR

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Fig. 2. Structogram of the levels and instruments of the spatial planning system in France.

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Planning systems in each country and sometimes federal states in Europe have a lot of common instruments and levels. The most common instrument in the European planning systems is the land use local plan (with sometimes different denominations), followed by the regional plan (focussing on regional development and regional structure). At least one local plan (land use, zoning plan) is legally binding, while plans from the upper levels can be legally binding or not. The scale can differ, especially as in different countries there are one, two or even three plans on municipal level. Also on regional level, plans are established on different scales, different administrative levels, and have also often different representations. For instance, plans in France are highly schematic and in Germany are very precise. Sometimes they are legally binding, sometimes not. Content is also different, depending of the country, like sectoral plans. Even in one state there may exist regions with plans and others without. Also the time of updating is an important fact which varies. On the national level, plans are established in different manner, depending on the political administration. [5]

There are many challenges for spatial planning in Europe - from heterogeneity of data to differences of planning legislations in the European countries. Infrastructure for Spatial Information in the European Community (INSPIRE) can significantly contribute to support spatial planning processes, especially in transboundary contexts. It should help to enhance exchange of strategic data, to improve the use of impact assessment and evaluation of plans and provisions in spatial planning with transparency and shared methodology.

References

1. Cerba, O., Charvat, K., Kafka, S., Mildorf, T. Spatial Planning – Example of European Integration of Public Data. In 7th Eastern European e-Gov Days: eGovernment & eBusiness Ecosystem & eJustice, 23-24. 4. 2009, Prague (Czech Republic).

2. Cerba, O., Charvat, K., Kafka, S., Mildorf, T. International Cooperation on Spatial Planning. In IST-Africa 2009, 6.-8. 5. 2009, Kampala (Uganda).

3. Plan4all – European Network of Best Practices for Interoperability of Spatial Planning Information, description of the work. [Online].Available: http://www.plan4all.eu/wk/images/e/e6/Plan4all_project_description.pdf

4. Directive 2007/2/EC of the European Parliament and of the Council of 14 March 2007 establishing an Infrastructure for Spatial Information in the European Community (INSPIRE). [Online]. Available: http://eurlex.europa.eu/JOHtml.do?uri=OJ:L:2007:108:SOM:EN:HTML.

5. Deliverable D2.1 Cluster of Leading Organisations in SDI for Spatial Planning. [Online].Available: http://www.plan4all.eu/wiki/Deliverables:public

6. Deliverable D2.2 Analysis of Innovative Challenges. [Online].Available: http://www.plan4all.eu/wiki/Deliverables:public

7. Deliverable D2.3 INSPIRE Requirements Analysis. [Online].Available: http://www.plan4all.eu/wiki/Deliverables:public

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8. Deliverable D2.4 User Analysis Report. [Online].Available: http://www.plan4all.eu/wiki/Deliverables:public

9. D2.5 Generic Conceptual model, INSPIRE Drafting Team “Data Specifications”. [Online]. Available: http://inspire.jrc.ec.europa.eu/reports/ImplementingRules/inspireDataspecD2_5v2.0.pdf

10. Data State of Play.[Online].Available: http://inspire.jrc.ec.europa.eu/reports/ImplementingRules/network/Data%20_State%20_of_Play_EUR_report.pdf

11. COMMUNICATION FROM THE COMMISSION TO THE COUNCIL, THE EUROPEAN PARLIAMENT, THE COMMITTEE OF THE REGIONS AND THE EUROPEAN ECONOMIC AND SOCIAL COMMITTEE, Green Paper on Territorial Cohesion. Commission of the European Communities. COM (2008) 616 final. [Online]. Available: http://ec.europa.eu/regional_policy/consultation/terco/paper_terco_en.pdf

12. Spatial development glossary. European Conference of Ministers Responsible for Regional/Spatial planning (CEMAT) 2007 (bilingual version) (Territory and landscape 2), Council of Europe Publishing. [Online].Available: http://www.coe.int/t/dg4/cultureheritage/Source/Resources/Publications/Land/CEMAT_Glossary_TerritoryandLandscapeNo2_BIL.pdf

13. INSPIRE documents. [Online].Available: http://inspire.jrc.ec.europa.eu/index.cfm/pageid/6

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GMES �eeds Described Spatial Data

Otakar Cerba

University of West Bohemia in Pilsen, Univerzitni 8, 306 14 Pilsen, Czech Republic, [email protected]

Abstract. The title of this chapter emphasizes a need of different types and levels of description of spatial data sets used for GMES purposes. Why? GMES is very large and not homogeneous initiative with brave targets (environmental questions, security etc.). The purpose of GMES is to deliver information which corresponds to user needs. The processing and dissemination of such information is carried out within the "GMES service component" (GMES – European Commission, 2009). To promote and maintain GMES activities we need a large number of tools, applications, methods and technologies.

Keywords: Spatial data, Spatial data description, GMES, Standardization, INSPIRE

1 Introduction

“GMES, which stands for Global Monitoring for Environment and Security, is a European programme for the implementation a European capacity for Earth observation. The main objective of GMES is to monitor and better understand our environment (How our planet is changing? Why is it changing? How this might influence our daily lives?) and to contribute to the security of every citizen. GMES will provide decision-makers who rely on strategic information with regard to environmental and security issues with an independent and permanent access to reliable data. The project aims at providing geo-information data on the regional, European and global scale and covers a wide range of thematic domains like Land use / land cover change, Soil sealing, Water quality and availability, Spatial planning, Forest management, Carbon storage, Global food security.” (GMES, 2009)

The title of this chapter emphasizes a need of description of spatial data sets used for GMES purposes. Why? GMES is very large and not homogeneous initiative with brave targets (environmental questions, security etc.). The purpose of GMES is to deliver information which corresponds to user needs. The processing and dissemination of this information is carried out within the "GMES service component" (GMES – European Commission, 2009). To promote and maintain GMES activities we need a large number of tools, applications, methods and technologies. But these instruments cannot work without good-quality data. As the

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information used and produced by GMES are related to specific locations we can talk about spatial data. Defining the term of spatial data is complicated. The complication is caused by the fact that except for the adjective “spatial” other attributes like geo-, geographic or geospatial are used. INSPIRE (Infrastructure for Spatial Information in the European Community) Glossary (INSPIRE Registry, 2009) defines the term “spatial data” as “data with a direct or indirect reference to a specific location or geographic area”. The functioning of the GMES is based on the availability of such data, the possibility of quick update, combination, exchange, visualization, analysis etc. Users also must have enough information about the data to be able to find data and decide if they are suitable for a particular purpose.

This chapter should answer three basic question related to using spatial data in the GMES framework.

1. Why should spatial data be described?

2. What is necessary to describe?

3. How is it possible to make spatial data description?

2 Importance of spatial data description

The strategic objective of GMES is to achieve harmonization of the fragmented national standards for global monitoring for environment and security throughout the European Union (Mirovsky, 2006). It is not a unification of standards on a single pan-European basis, but the harmonization and interconnection of existing resources, including spatial data. Such harmonization needs the huge number of knowledges and information on harmonized elements. Therefore especially semi-automated or full-automated harmonization must be supported by such information and knowledges extracted from concrete spatial data sets and from other external sources describing these spatial data sets.

It should be noted that the activities related to GMES related not only to current all-European spatial data. Activities relating to environment and security use the large number of different spatial data sets, which differ from each other.

• Data from various makers (state authorities, commercial companies,

public - collaborative mapping)

• Data from various providers

• Data provided under different licenses and legislative restrictions

• Data using different data models

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• Data provided in various data formats

• Data acquired in various ways (satellite imagery, photogrammetry, public /collaborative/ mapping, state administration mapping, GPS measuring but also information like text documents, photos, statistical documents, historical and archive materials)

• Data of different ages (from historical documents to actual remote sensing data)

• Data in different dimensions (2D, 2,5 D, 3D, temporal components)

• Data at different scales

• Data covering different areas (from a global perspective like Earth browser to a specific interiors of buildings and utility lines)

The set of users of spatial data from GMES is also very complicated in terms of harmonization. These data sets could be used by public, risk management and security bodies, forest and water management, industry, state administration etc. Moreover, it is necessary to emphasize linguistic and cultural differences, traditions, and national or local standards related to acquisition of spatial data set, their processing and cartographic visualization. The term user does not refer only to humans, but also to machines. More precisely, various automated processes like search or visualization services represent GMES users, too.

We could find many other characteristics of spatial data (e.g. spatial reference systems or portrayal rules – see Directive 2007/2/EC), which further accentuate the differences of individual data sets and limit the harmonization process. Any method of unification of all data sources is impossible for many reasons – the number of data is very high and still increasing, questions of national legislatives, using of different hardware platforms, operational systems and software products with proprietary formats and models etc. Harmonization of GMES and other data sets must be provided through existing data sets description and following particular transformation and/or conversions and not through existing data sets transformation to one platform. Only detailed multilevel spatial data description enable to find, decode and apply information and knowledges to use, share and combine different data. The importance and significance of this approach based on information and knowledges on spatial data sets increase with need of very fast acquisition of very quality data, for example for purposes of risk management or security.

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3 Spatial data components and properties

What is it mean to describe spatial data sets? The description should be based on interconnected description of spatial data components and attributes. This description is mostly explicit and external. But for example data coded in a mark-up language can have some internal description by tags marked the meaning of elements and attributes.

Spatial data have a large number of different properties which could be divided into 4 groups. This selection of properties is based on following publications – (Annoni et al., 2008), (Cada & Mildorf, 2005), (Cerba & al., 2009b), (Directive 2007/2/EC), (ISO 19115:2003):

1. Common properties of data: Support of interoperability and accessibility (Multilinguality, Cultural adaptability, Metadata, Legislative conformance, Relationships to other data, Data models), Data origin (Data character /measure or processed data/, Methods used for data capture, Data management, Frequency of updating, Types of updated information), Data distribution (Licenses, Prices, Data providers or distributors), Data presentation (Visualization model, Multiple representation), Technical parameters of data storage and distribution (Medium, Data format)

2. Properties of spatial components of data: Used units, Precision, Granularity, Consistency, Reliability, Spatial scope, Geometry (spatial representation), Dimension, Topology, Geodetic datum

3. Properties of temporal (time) components of data: Used units, Precision, Granularity, Consistency, Reliability, Time scope.

4. Properties of attribute (descriptive) components of data: Used units, Precision, Granularity, Consistency, Reliability, Theme of attributes, Terminology, Classification systems, Identifier management, Registries, Feature catalogues (description of attributes).

4 Standards represent the right way

When does anybody ask how to describe spatial data, there is only one correct answer – using standards. There are many different standards, methods, technologies and applications describing various components of spatial data at different levels of the model. The following table (based on document Niemann, 2005) gives an overview of these forms and relevant standards.

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Table 1: Spatial data description methods

Standard Level of model

Controlled vocabularies & glossaries Thesauruses

Relation models, mark-up languages

ER model, DB Schema, XML schema languages Taxonomies

Topic Maps Conceptual models

RDF/S

UML

Ontologies Logical theories

Description Logic

First Order Logic

Modal Logic

Axiology

All of the above models and methods may be described in detail by using metadata standards (e.g. ISO 19115, some other component of the series of ISO 191XX or Dublin Core Metadata Initiative.

5 Conclusion

GMES is among the projects of the very near future. Near future, however, in terms of information and communication technologies (ICT) is the arise of new technologies, bringing significant changes for example possibilities of:

• Composition of different services and data sources located on remote computers

• Individual profiles related to spatial data and their representation, for example culturally specific or language specific profiles

• Using of contexts of current situation

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• On demand data – user will get only necessary data to make the all process more faster

Harmonisation of spatial data could have another benefits to data users (except possibilities of using of new technologies):

• Any duplicities in data

• Clear origin and assurance of quality of the data

• Data structure standardisation

• Data purity, security and structure uniformity

• Better data manipulation

• Reciprocal data accessing per WMS (Web Map Service), WCS (Web Coverage Service) and WFS (Web Feature Service) – preservation data up-dating (possibility of on-line actualisation)

• Fall of cost for data updating and maintenance

• Better software development

• Better source exploitation

• Improvement of chances in communication with authorities

• Better utilization and commercialization of urban planning geospatial data

• Increasing activities, e.g. education (Cerba et al., 2009a)

All of these processes will require spatial data and the demands on quality of these data will be constantly rising. Therefore it is necessary the implementation of different methods and levels of spatial data description. Similarly to the initiative for the complete validation called Document Schema Definition Language (DSDL) a structure for describing and exchanging not only spatial data should be designed. Because the only way of interconnected group of methods of spatial data description bring the higher spatial data accessibility and interoperability. It is necessary for such large projects like GMES or INSPIRE. Spatial data description could be applied in designing and building of an expert system. For example one of such expert systems could design and technique of cartographic spatial data visualization based on knowledges and information about spatial data.

There are four main factors to push to the integration in spatial data (according to Cerba et al., 2009a):

1. Legislative rules and their strict control.

2. Business strategies (requirements of market).

3. Education – explanation of benefits of approach based on spatial data description.

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4. Quality of technical support and development of new technologies supported standards.

References

1. Annoni, A., Friis-Christensen, A., Lucchi, R. & Lutz, M. (2008). Requirements and Challenges for Building a European Spatial Information Infrastructure: INSPIRE. In van Oosterom & P., Zlatanova, S. Creating Spatial Information Infrastructures. Towards the Spatial Semantic Web. CRC Press, Taylor & Francis Group, London. ISBN 978-1-4200-7068-2.

2. Cada, V. & Mildorf, T. (2005). Delimitation of reference geodata from land data model. GIS Ostrava 2005. Ostrava: VŠB - TUO, 2005. s. 1-12. ISSN 1213-239X.

3. Cerba, O., Charvat, K., Kafka, S. & Mildorf, T. (2009a). Spatial Planning – Example of European Integration of Public Data. Paper presented at 7th Eastern European e|Gov Days: eGovernment & eBusiness Ecosystem & eJustice, April (22) - 23 - 24, 2009 Prague, Czech Republic.

4. Cerba, O., Charvat, K., Jezek, J., Kafka, S. & Musil, M. (2009b). Spatial data interoperability makes ICT use more efficient.

5. Directive 2007/2/EC of the European Parliament and of the Council of 14 March 2007 establishing an Infrastructure for Spatial Information in the European Community (INSPIRE). (2007)

6. GMES – European Commission (2009). Retrieved November 16, 2009 from http://ec.europa.eu/gmes/index_en.htm.

7. GMES. (2009) Retrieved November 16, 2009 from www.gmes.info. 8. Geographic information — Metadata. Information géographique — Métadonnées .

ISO 19115:2003. (2003), ISO. 9. INSPIRE Registry. Glossary. European Commission, 1995-2009. (2009) Retrieved

September 15, 2009, from http://inspire-registry.jrc.ec.europa.eu/registers/GLOSSARY.

10. Mirovsky. O. (2006). Co je program GMES?. Czech Space Office. Retrieved November 16, 2009 from http://www.czechspace.cz/cs/gmes.

11. Niemann, B. (2005). Data Reference Model Implementation Through Iteration and Testing Version 1.0. Retrieved November 19, 2009 from http://web-services.gov/DRMITIT10172005.doc.

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GMES – The European ambition to bring Earth

Observation capacities in daily use

Ondrej Mirovsky

Czech space office, Katerinská 10, Prague 2, 128 00, Czech Republic, [email protected]

Abstract: Following paper describes evolution and recent development of the GMES programme, which is a European tool how to bring data produced within earth observation capacities closer to daily use for numerous international, national and even regional institutions. Global Monitoring for Environment and Security (GMES) will help to ensure sustainable flow of accurate and timely data to monitor changes of our environment and will be a helpful tool to manage and coordinate fast emergency response.

Keywords: GMES, European Union, European commission, European Space Agency, European Environmental Agency, services, data, environment, security.

1 Introduction

The planet Earth is recently going through ages of rapid change of its surface, biosphere, atmosphere and climate, which has impact on both nature and people inhabiting this planet. In order to be able to monitor these changes, Earth Observation (EO) gives us powerful tool how to get detailed information on global scale in a short of time.

European Union is in terms of environmental issues global leader and needs accurate and timely information to fulfil all monitoring and reporting demands as well as data for quick emergency response. Therefore, GMES (Global Monitoring for Environment and Security) as the European Initiative for the establishment of a European capacity for Earth Observation was launched.

2 GMES – first steps

A key driving element having contributed to the establishment of GMES was the paradox of having so much data produced within current Earth Observation systems on one hand and lack of good quality and timely data delivered to

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decisions makers on the other hand. Thus, in 1998 in Baveno (Italy) representatives of numerous institutions in this field concluded together with European commission and European Space Agency to establish European capacity for Earth observation named GMES.

However, it was not only need to ensure data for Europe, but GMES bears also greater geostrategic importance of having autonomous system not dependent on non-European systems, where still now EU depends almost from 60% on foreign EO systems. EU commitment in this field is also a good tool to support European spaces industry, research and development while are all targeting to help to meet goals of the EU Lisbon strategy.

During last few years GMES has received wider importance within EU and in 2004 GMES was recognized in the Communication from the Commission to the European parliament and the Council /COM (2004) 65/(1) followed by the resolution of the Parliament giving “green” light to further develop GMES. Further on GMES found substantial basis to its development via finances from Seventh Framework Programme (FP7) in the domain of SPACE research. In the period 2007- 2013 some 1.2 billion EUR were made available to develop GMES.

3 Architecture of GMES

The GMES initiative federates a wide range of observational networks and data providers, exploiting the most recent observation techniques and technologies, for developing edge-cutting information products to end-users. In principle, the GMES observational infrastructure composes of two main components – space and in situ.

Space infrastructure

The space component shall ensure sustainable provision of satellite derived Earth observation data to all GMES services. The architecture of the component is derived from service requirements provided by the user communities. ESA and EUMETSAT are two main European actors in this area who should play the major role in co-ordination, implementation and operational running of the infrastructure (2).

Key elements of this component will be sets of 6 satellites systems named Sentinels, which shall cover all space born data needs for all services. These satellites will acquire radar and optical data, information on atmospheric chemistry and many other needs. First satellites on the orbit are expected in 2011. It is also a key aspect of benefits of GMES programme that Sentinel satellite systems are synergic logical follow up of some already existing satellite systems widely used in Europe (e.g. SPOT and ENVISAT).

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Fig. 1. Sentinel 1 (source ESA)

In-situ infrastructure

The in situ component is based on an observation infrastructure owned and operated by the large number of stakeholders coordinated, in some cases, in the frame of European or international networks. In situ observation activities and associated infrastructure derive from a range of national, EU and international regulatory requirements and agreements or form part of research processes. None was created to meet the needs of GMES, and they cover a much wider field than the GMES services. By this reason European Environmental Agency was appointed to co-ordinate the consolidation of in-situ networks for GMES purposes (2).

Users Third key element of GMES are surely users. Users are here to define their needs to both space and in-situ elements in order to get from the system such data they can instantly use for their daily needs. User-driven principle shall be applied in both elements – for the design of satellite systems as well as on in-situ data processing to final users. What European users need most are ready-made tailored data.

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Fig. 2. GMES architecture (source EC)

4 GMES services

Bringing GMES into reality of daily life involves sets of services, which are now in pilot phase with the future transition into operational services. Today we have five basic GMES services under development tackling most needed information for European users.

Land monitoring service is now being developed under GEOLAND 2 project and it is dedicated to cover land monitoring needs for Europe including topics as land cover changes, agri-environmental issues, spatial planning, forest monitoring etc. For the domain of marine applications project MyOcean is now processed to cover monitoring of the ocean and seas in order to get better data on maritime security, natural recourses, oil spill prevention etc (3.) Emergency response service of GMES is covered by project SAFER which gathers activities towards to a rapid mapping and provision of online information during emergency situations. The scope of this service goes even on global level, when this service has the potential to work worldwide. Atmosphere services of GMES are recently under MACC project, when core of this task is to deliver data on air quality, climate change, monitor sand and dust storms, UV radiation risks etc. Lastly, G-MOSAIC

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project is now running to cover security GMES services. Core of activities is in the provision of geo-spatial information in support of EU external relation policies for Security related activities (4).

5 GMES – operational service

After ten years of research activities, GMES has now entered its pre-operational phase through five major projects (as listed above) financed by the EU, ESA and Member States budgets aimed at developing future operational services and infrastructure. The services are being developed to meet the needs of a wide range of users who rely on accurate environmental and security data and information. Operational, continuous and sustainable delivery of information has not yet been achieved. Further investment is therefore necessary, in Space infrastructure in particular, in order to fill the remaining gaps in GMES services and to guarantee their long-term sustainability and reliability. In addition, a common approach between the various partners involved in the development of GMES needs to be further enhanced, to avoid the possibility of a duplication of efforts. GMES is also creating opportunities for increased private sector usage of new information sources. It will trigger partnerships between research and service providers, many of them small and medium enterprises. Thus, while not likely in the short to medium term, the development of market opportunities could eventually determine the proportion of public investment (5).

This year regulation on the European Earth observation programme (GMES) and its initial operations was adopted to guarantee smooth transition from research phase into operational phase of GMES before the new financial perspective of the EU will be in place.

6 Conclusion

Earth Observation encompasses a powerful set of advanced technologies which in combination with in situ (ground-based, airborne etc.) measurements provides products and services supporting solutions to international challenges such as security threats, environmental degradation and climate change. The GMES initiative reflects the European decision to develop its own, independent observation capabilities. At this time GMES stands on the edge of transition into real operational services delivering data where needed and has a unique potential to be a very successful approach how to maintain our planet safe and healthy. For its success, future strong commitment of its main key players – European Commission and European Space Agency is needed together with the voice of member states of the EU and other international bodies.

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References

1. COM (2004) 65, COMMUNICATION FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT AND THE COUNCIL, Global Monitoring for Environment and Security (GMES): Establishing a GMES capacity by 2008 - (Action Plan (2004-2008))

2. http://ec.europa.eu/gmes/obser_infra.htm 3. http://www.myocean.eu.org/index.php/project/objectives 4. http://www.gmes-gmosaic.eu/ 5. Kolar, J., Mirovsky, O. (2009): The Czech EU presidency: a gateway to 6. GMES for users from Central and Eastern Europe, Window on GMES,

March 2009, ISSN 2030-5410, http://www.boss4gmes.eu/index.php?id=103&no_cache=1

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Spatial Observation Services and Infrastructure in the

Czech Republic – SOSI CZ

Lukas Brodsky1, Milan Novacek2, Jan Kolomaznik1, Vaclav Vobora1, Lubos Kucera1

1GISAT spol. s.r.o., Geoinformation Company, Charkovska 7,

101 00Praha 10, Czech Republic {Lukas.Brodsky, Jan.Kolomaznik, Vaclav.Vobora, Lubos.Kucera}@gisat.cz

2ANF DATA spol. s r. o., Pujmanové 1221, 140 00 Praha 4, Czech Republic [email protected]

Abstract. The SOSI CZ project is one of the three related SOSI (Spatial Observation Services and Infrastructure) projects, each implemented in a different country. The overall multi-country SOSI project was initiated by ESA with the aim to demonstrate the innovative technology and service concepts within the context of the European Shared Environmental Information System (SEIS). Profiting from the ESA developed technology and the availability of ESA Service Support Environment (SSE), which is a Web-service based system supporting chaining of distributed services, the entire SOSI project aims at demonstrating the possibility to create a network of service provision points supporting at the same time needs at various levels: from local to European, like those of the European Environmental Agency (EEA). In addition to the above-mentioned SOSI common objectives, SOSI CZ focuses on implementation of a satellite imagery dissemination service and implementation of MEEO Software Modules for automated pre-classification of satellite imagery.

Keywords: Spatial Observation Services, Earth observation, SEIS, SSE, Land Cover

1 Introduction

SEIS – a European Perspective

According to the European Union’s 6th Environmental Action Programme aiming at a Sustainable Development Strategy integrated assessments of environmental information are becoming the trend. This nurtures the vision of a Shared Environmental Information System (SEIS) with the scope to improve, modernise,

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streamline, and connect environmental information systems in Europe and world-wide (see Ref. EEA, 2008). From the European Environment Agency’s (EEA’s) perspective (Steenmans, 2009) SEIS is about:

• Sharing (organisation): Political commitment (legislation); Partnership (win-win); Networking (connecting);

• Environmental Information (content): Horizontal integration (data centres); Vertical integration (local to global); Online access - real time for policy makers and public;

• System (infrastructure and services): Existing ICT Infrastructure; INSPIRE, Report net, GMES, etc.; New e-Services (e-Government).

In this list the SOSI project addresses primarily the items “networking”, “online access” and all items under “System”, i.e. Europe's infrastructure backbone for environmental services.

SOSI Common Objectives: • Identifying land monitoring information services common to all

participating countries and relevant at local and European levels

• Implementing in each participating country a Service Provision Point integrating relevant technology

• Implementing a SOSI Demonstrator overarching through SSE all the Service Provision Points

• For the identified land monitoring information services, verifying that the SOSI Demonstrator permits both - their local use with local flavours and also integrated use in a wider European context (in particular towards the EEA)

SOSI CZ Objectives: On top of SOSI common objectives the SOSI CZ will also focus on:

• Implementation of satellite imagery dissemination service (including data archiving and cataloguing)

• Implementation of MEEO Software Modules for automated pre-classification (including validation and benchmarking) of satellite imagery.

2 Project Description

SOSI is a project for developing innovative “Spatial Observation Services and Infrastructure” within the context of land monitoring initiatives at European and Member State levels. The project’s objective is to demonstrate, in real operations, a decentralized information system allowing integration of distributed data and

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processing services as well as access and distribution at multiple levels, languages and content granularities.

SOSI is contributing to and maintaining - during a demonstration period - a network of test implementations intended to be jointly operated by the European Space Agency (ESA), the European Environment Agency (EEA) and the participating organizations from the European Member States Austria, Czech Republic, Hungary and Luxembourg. The programmatic objectives of the European Shared Environmental Information System (SEIS) and related user requirements are providing orientation to SOSI. In particular the SEIS activity to implement the Land Cover Data Service (LCDS), a joint initiative of EEA [RD07] and twelve Member States to establish an information sharing and reporting environment for land use and land cover change, will be addressed by the SOSI project. It is expected that the results of the SOSI project will contain valuable recommendations for the future evolution of these European services.

The primary technology and operational procedures of SOSI are being implemented by utilizing the Service Support Environment (SSE) of ESA [AD03]. SOSI offers a distributed node-based infrastructure of Web-services following Service Oriented Architecture (SOA) principles and standards thus establishing access to a number of content services (Figure 2) and one land cover generation processing service operated by the participating organizations. The SSE infrastructure is providing coupling and user access mechanisms (binding, workflows and portal).

Further programmatic facets come into the SOSI project by the fact that some of the very first operational products of Kopernikus, Europe’s Global Monitoring for Environment and Security initiative (former GMES), have been loaded and made accessible via the SOSI infrastructure. The product’s official name is "High resolution core land cover data for built-up areas, including degree of soil sealing, 2006" which was generated in the course of the "GMES Fast-Track Service on Land Monitoring" project spearheaded by EEA with coordinated satellite data provisioning by ESA.

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Fig. 1. SOSI Servers in Member States and at European Agencies.

In addition, the SOSI system offers on-line access to the "Corine land cover map 2000" (CLC2000) dataset, the product of an EEA coordinated activity with Member States. This dataset includes land cover data of lower spatial and thematic but high temporal resolution, semi-automatically derived from MERIS instrument data received by the local Envisat receiving station in the Czech Republic. Data on land cover is necessary for formulating environmental policy as well as for other purposes such as regional development and agriculture policies. At the same time it provides one of the basic inputs for the production of more complex information on other themes (soil erosion, pollutant emissions into the air by the vegetation, etc.).

The SOSI project foresees to implement an operational service to demonstrate online access to this high resolution data for built-up areas entirely covering four pilot states, namely: Austria, Czech Republic, Hungary and Luxembourg (Figure 1). This land cover data (LC data) will be provided at connected service provision points physically operated in each of these countries. Potentially more areal coverage can be accessed via the service provision points operated by the EEA node called Land Use Data Centre (LUDC), which is also planned to be interfaced by the SOSI infrastructure.

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In the course of analysing the contributions from the mentioned Member States a proposal to tackle also specific national requirements has developed: The Hungarian participation in the information network will, in addition to the land cover service setup in Hungary, address multi-lingual aspects of a national portal for Hungarian users. This is expected to challenge SSE configuration flexibility in international scenarios. The plans for the SOSI implementation in the Czech Republic (CZ) foresee that an existing Earth Observation (EO) satellite data archive maintained nationally for regionally received Envisat MERIS data shall be connected via SSE drawing benefits from the available tools for publishing archive data, discovery, viewing, ordering via a powerful graphical user interface, and secure delivery of data to users.

Fig. 2. SOSI Service Metamodel.

The SSE capabilities of setting up workflows and value chains of distributed services are a further demonstration objective in SOSI. A custom automated Land Cover (LC) generation engine provided by the company MEEO shall be installed as a network service which can be chained into a SOA workflow. The experimental configuration in SOSI shall demonstrate at least the availability of manually LC processed data from the Czech archive service and the flow via this LC generation engine to the Czech LC provider service. It is expected from this demonstration that the value adding process may be in the future managed in a widely automated way, incorporating both synchronous and asynchronous (e.g. for human operator intervention) steps in the processing and provisioning chain, as

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required. Also the performance and behaviour of the MEEO classification engine shall be assessed.

All in all, it is hoped that the SOSI activity will be convincing that the envisaged SOA approach incorporates a set of viable and efficient tools which can favourably be used for the implementation of “ubiquitous access to distributed, cooperating data and services”, by demonstrating service examples in the EO land monitoring application field.

Acknowledgments. The project is conducted under contract of the European Space Agency ESA (ESRIN Contr. No. 21776/08/IL-G) and CZ national PECS program (Contract number 98082 – “SOSI CZ Spatial Observation Services and Infrastructure in the Czech Republic”) with strong steering support by the European Environment Agency EEA. The authors wish to thank Mr. S. D’Elia, Mr. A. della Vecchia and Mr. P.G. Marchetti from ESA as well as Mr. J. Bliki, Mr. S. Jensen, Mrs. A. Sousa, Mr. C. Steenmans, and the LUDC team from EEA for essentially having formed the project idea and for accompanying its execution. The preparedness by the company Geoville to host the Luxembourg SOSI instantiation is very much appreciated. The contributions of the company Spacebel regarding SOA and SSE knowhow and of the company MEEO regarding automated LC generation and practical SSE knowhow have been very valuable to the SOSI project.

References

1. EEA – European Environment Agency, Shared environmental information system, 2008, http://www.eea.europa.eu/about-us/what/shared-environmental-information-system.

2. ESA – European Space Agency, Service Support Environment, 2008, http://services.eoportal.org.

3. JRC – Joint Research Centres, INSPIRE Technical Architecture – Overview, V1.2, 2007, http://inspire.jrc.ec.europa.eu/reports.cfm.

4. JRC – Joint Research Centres, INSPIRE Network Services Architecture, V3.0, 2008, http://inspire.jrc.ec.europa.eu/reports.cfm.

5. Steenmans, C., Towards a Shared Environmental Information System, SEIS – A European perspective, European Environment Agency Presentation, 2009.

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The Black Sea Catchment Observation System built on a

grid-enabled Spatial Data Infrastructure

Anthony Lehmann1,2, Gregory Giuliani1,2, Nicolas Ray1,2, Karin Allenbach1,2,

Karel Charvat3, Dorian Gorgan4, Mamuka Gvilava5, Tamar Bakuradze5, Seval Sozen6, Cigdem Goksel6 and the enviroGRIDS consortium

1University of Geneva, enviroSPACE, Battelle Bat. D, Route de Drize, CH-1227 Carouge, Switzerland

2UNEP/DEWA/GRID-Europe, Switzerland 3 Czech Centre for Science and Society, Czech Republic

4 Technical University of Cluj-Napoca, Romania 5 GIS & RS Consulting Center "GeoGraphic", Georgia

6Istanbul Technical University, Turkey

Corresponding author: [email protected]

Abstract. The Black Sea catchment represents a very large historically rich area of more than 2 million km2 with more than 160 million inhabitants occupying a strategic position between Europe and Asia. It is partially following an unsustainable development caused by inadequate resource management that leads to severe environmental, social and economical problems. The EnviroGRIDS @ Black Sea Catchment project is addressing these issues by bringing several new emerging information technologies that are totally revolutionizing the way we will be looking at our planet in the future. The Global Monitoring for the Environment and Security (GMES) and the Global Earth Observation Systems of Systems (GEOSS) are indeed building a data-driven vision of our planet to explore its past, present and future. The INSPIRE directive is promoting data sharing through interoperability standards at European level, while the UN-SDI is following the same pathway within the United Nations. In order to address the challenges faced by these initiatives of increasing need for data storage and processing, enviroGRIDS will build upon the largest Grid computing infrastructure in the world (EGEE) that will transform elements of software underpinning scenarios and models onto a gridded system. EnviroGRIDS is aiming at building the capacity of scientist to assemble such a system, the data providers to share their data, the capacity of decision makers to use it, and the capacity of the general public to understand the important environmental, social and economical issues at stake.

Keywords: GEOSS, GMES, INSPIRE, UNSDI, EGEE, Black Sea catchment, SWAT, remote sensing, sensors, interoperability, grid-enabled Spatial Data Infrastructure.

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1 Introduction

The enviroGRIDS project aims at building capacities in the Black Sea region on new international standard to gather, store, distribute, analyze, visualize and disseminate crucial information on past, present and future states of this region in order to assess its sustainability and vulnerability. In order to achieve its objectives, enviroGRIDS will build an ultra-modern grid-enabled Spatial Data Infrastructure (GSDI) using web services to connect to the Global Monitoring for the Environment and Security (GMES) and the Global Earth Observation System of Systems (GEOSS). It will be also fully compatible with the EU directive on Infrastructure for Spatial Information in the European Union (INSPIRE) and the equivalent UN initiative (UN-SDI).

The scientific aim of the enviroGRIDS project is to promote and federate existing Observation Systems in order to address several Societal Benefit Areas as defined by GEOSS within a changing climate framework. This system will incorporate a shared information system that operates on the boundary of scientific/technical partners, stakeholders and the public. It will contain an early warning system that will inform in advance decision makers and the public about risks to human health, biodiversity and ecosystems integrity, agriculture production or energy supply provoked by climatic, demographic and land cover changes on a 50 year time horizon.

The generic technical objectives of the enviroGRIDS project are to:

• Run a gap analysis on existing regional observation systems to prepare recommendations for improvement of networks of data acquisition in each region/country

• Improve regional network to coordinate the efforts of partners active in observation systems

• Develop the access to real time data from sensors and satellites

• Create spatially explicit scenarios of key changes in land cover, climate and demography

• Distribute large calculations and datasets on large computer clusters (Grid)

• Streamline the production of indicators on sustainability and vulnerability of societal benefits

• Provide policy-makers and citizens with early warning and decision support tools at regional, national and local levels

• Build capacities in the implementation of many new standards and frameworks (INSPIRE, GEOSS, GMES, UN-SDI)

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2 Background

The core environmental problem of the Danube River Catchment can be described as “ecologically unsustainable development and inadequate water resources management” [1]. The problems are caused by different factors, such as: inadequate management of wastewater/solid waste, ecological unsustainable industrial activities, and inadequate land management and improper agricultural practices. These factors generate several direct consequences: pollution of surface/groundwater, eutrophication, and accelerated runoff /erosion. These consequences have in turn the following main effects: decline in quality of life, human health risks, degradation of biodiversity, economic decline, and reduced availability of water. The Black Sea itself is also affected by severe environmental degradation [2]. Some signs of recovery have been observed in the last years, but eutrophication remains a severe problem.

Several of the environmental topics addressed in enviroGRIDS are clearly related and interdependent. As climatic change is becoming a worldwide concern that will affect many areas of human activities, the last report of the Intergovernmental Panel on Climate Change [3,4,5] predicts important changes in the coming decades that will not only modify climate patterns in terms of temperature and rainfall, but will also drastically change freshwater resources qualitatively and quantitatively, leading to more floods or droughts in different regions, lower drinking water quality, increased risk of water-borne diseases, and irrigation problems. These changes may trigger socio-economic crises across the globe that need to be addressed well in advance of their occurrences in order to reduce their associated risks.

Indeed, as documented by several assessments, humans are exerting significant impacts on the global water system [6] through activities such as the modification of the hydrological cycle, the accelerated melting of snow and ice in alpine zones, the removal of trees that lead to increased runoff, reduced transpiration, impacts on the water table and landscape salinity, the draining of wetlands, irrigation for agriculture, the alteration of flow through dams, the transfer of water between catchments, and pollution from industrial, agricultural and domestic sources.

The European Community is addressing the crucial problem of water quality and quantity by adopting the Water Framework Directive [7] that promotes water management based on watersheds rather than administrative or political boundaries. The aim is to build river catchment management plans that define objectives based on ecological, hydrological and chemical values, as well as protected areas status. River catchment analysis will integrate the analysis of the economic value of water use for stakeholders in order to understand the cost effectiveness of alternative policy and technical measures. However, despite efforts to date, the vulnerability of different areas of Europe and beyond to climate change remains poorly addressed. The United Nations has followed a similar

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pathway and launched the UN Water Program [6] that aimed at bringing a greater focus on water-related issues at all levels and on the implementation of water-related programmes in order to achieve the water-related targets in Agenda 21, the Millennium Development Goals (MDGs) and the Johannesburg Plan of Implementation (JPOI).

3 EnviroGRIDS consortium

The enviroGRIDS partners cover expertise in several fields of environmental sciences and information technologies. They have a very strong and direct interest in Observations Systems and have connections in numerous local, national, regional and international organisations. Together they form a very strong consortium that will be able to raise significantly the Public awareness in different Societal Benefits Areas, to build Decision Makers capacity to use Observation Systems, and Scientists capacity to construct them and feed them with quality information.

This consortium will be supervised from Geneva that occupies a strategic position by hosting several international organizations centered on environmental and related societal issues (GEO, UNEP, UNDP, WHO, WMO, WCO, ICRC, IUCN, WWF…). Indeed, the Group on Earth Observation (GEO) intergovernmental project is based in Geneva to establish the Global Earth Observation System of Systems that is recognized by the European Commission as an official partner for global projects. The United Nations Environment Programme (UNEP), through its GRID-Europe office, has a long experience in gathering and making available global environmental data through, for instance, the Global Environmental Outlook program, and is presently involved in project on the climatic vulnerability of the shallow Lake Balaton in Hungary as well as several other European projects. The Enabling Grids for E-Sciences project (EGEE) that is coordinated by our CERN partner will provide the necessary computing and storage capacity for this project. The Climatic Change and Climate Impacts group at the University of Geneva has an excellent international reputation in terms of its research on climate change impacts and is striving to reinforce its relationships with international organizations. Therefore, the combined expertise of GRID, UNIGE, CERN and GEO will be easy to gather regularly to guarantee the best possible steering of the enviroGRIDS project.

Many partners in this project are leaders in the field of hydrological modeling and already know each other because they belong to the active community of users of Soil and Water Assessment Tool (SWAT, Arnold et al., 1998), and have already collaborated in other projects. The UNESCO Institute for Water Education (IHE) is a leading institute in research and teaching hydrology for students coming from the entire world. The Swiss Aquatic Research Institute (EAWAG) is an internationally recognized research institute in hydrology and has done some large

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scale uses of SWAT in recent years for instance across the entire African continent or in Iran. The University of Barcelona (UAB) is partner within the European Topic Centre on Land Use and Spatial Information (ETC-LUSI). Finally, the Centre for Advanced Studies, Research and Development in Sardinia (CRS4) is also a leading partner in information and technology and started to develop web based decision support tools based on SWAT outputs.

This strong hold of Western Europe partners is ideally reinforced in the enviroGRIDS project with several high level education, research, public and private partners within the Black Sea Catchment. For example, IBSS (Ukraine) is one of the leading institutes in terms of the long-term research of the Black Sea ecosystem. IBSS holds and develops the database on over 150 oceanographic expeditions dealing with this region. Along with USRIEP (Ukraine), DHMO (Ukraine), SPSU (Russia), DDNI (Romania) these institutes have monitored the ecosystems of the Black Sea, the Sea of Azov, the Danube delta, and forecasting the present ecological state of marine and terrestrial components of the catchment. INHGA (Romania) has a long-standing experience in water resources, flood and drought risk management, as well as the assessments of the impact of human activity and climate change on the hydrological regime of the catchment. GeoGraphic (Georgia) develops specialized software, flexible data management technologies, and cartographic production pertained to the environmental issues of the Black Sea region. Finally, CCSS (Czech Republic) is a leading center in Spatial Data Infrastructure and sensors deployment.

Table 1. The enviroGRIDS consortium.

Beneficiary name Short

name

Country

Université de Genève UNIGE Switzerland Czech Centre for Science and Society, partner of United Nations Spatial Data Infrastructure

CCSS Czech Republic

European Organization for Nuclear Research (CERN) CERN Switzerland (Int.)

Swiss Federal Institute of Aquatic Science and Technology

EAWAG Switzerland

Geographic GIS&RS Consulting Center Geographic Georgia UNESCO: Institute for Water Education IHE The

Netherlands (UN)

University of Barcelona, European Topic Centre Land Use and Spatial Information supported by the European Environment Agency (EEA)

UAB Spain

Ukrainian Scientific and Research Institute of Ecological Problems

USRIEP Ukraine

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Soresma n.v. SORESMA Belgium St. Petersburg State University SPSU Russian

Federation Istanbul Technical University ITU Turkey Melitopol State Pedagogical University and Azov-Black Sea Ornithological Station

AZBOS Ukraine

ArxIT consulting ARXIT Switzerland Black Sea Regional Energy Centre BSREC Bulgaria Danube Delta’ National Institute for Research and Development

DDNI Romania

Danube Hydrometeorological Observatory DHMO Ukraine Institute of Biology of the Southern Seas IBSS Ukraine Institute of Geography of the Romanian Academy IGAR Romania National Institute of Hydrology and Waters Management

INHGA Romania

Odessa National I.I. Mechnikov University ONU Ukraine Technical University of Cluj-Napoca UTC Romania Environmental Protection and Water Management Research Institute

VITUKI Hungary

Permanent Secretariat of the Commission on the Protection of the Black Sea against Pollution

BSC PS Turkey

Advanced Studies, Research and Development in Sardinia

CRS4 Italy

International Commission for the Protection of the Danube River

ICPDR Austria

National Institute of Meteorology and Hydrology NIMH Bulgaria Tavrida National University TNU Ukraine

4 EnviroGRIDS step by step

First, a gap analysis will allow identifying areas where most efforts are needed to reinforce existing observation systems in the Black Sea catchment. Then, spatially explicit scenarios of key drivers of changes such as climate, demography and land cover will be created. These scenarios will feed into hydrological models calibrated and validated for the entire Black Sea Catchment. EnviroGRIDS will rely on the largest grid computing infrastructure in the world (EGEE) that will transform elements of software underpinning scenarios and models onto a gridded system. The combined impacts of expected climatic, demographic, land cover and hydrological changes will be measured against GEOSS Societal Benefit Areas through several pilot studies in different countries within the Black Sea catchment. A strong effort will be put on convincing regional data holders to serve their metadata and data through web services in order to complement the global data made available by several international organizations. Specific outcomes will be analyzed and made accessible through a state-of-the-art web interface. The resulting web services will help our main targeted end users, the Black Sea

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Commission and the International Commission for the Protection of the Danube River, to improve their web portal for their communication on the state of the Black Sea catchment (Figure 1).

Fig. 1. EnviroGRIDS data flow and processing based on web services and regionally and internationally available data to serve principal end users needs, public and decision

makers.

5 Soil and Water Assessment Tool

New advances in computing technology plus data availability from the Internet have made high resolution modelling of distributed hydrologic processes possible. Using the program Soil Water Assessment Tool (SWAT) [8] (http://www.brc.tamus.edu/swat/), enviroGRIDS will apply a high-resolution (sub-catchment spatial and daily temporal resolution) water balance model to the entire Black Sea Catchment (BSC). The BSC Catchment (Figure 2) model will be calibrated and validated using river discharge data, river water quality data, and crop yield data [9]. As part of the modelling work, uncertainty analysis will also be performed to gauge the confidence on all model outputs. Subsequent analyses of land use change, agricultural management change, and/or climate change can then predict the consequence of various scenarios.

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An example of the use of SWAT can be found in the “Lake Balaton Integrated Vulnerability Assessment, Early Warning and Adaptation Strategies” project that was launched following many years of water quality problems and a negative water balance induced by water shortage starting in 2000 and lasting for four years [10]. This raised a serious sustainability concerns in the Lake Balaton area, Hungary and the region. Due to the Lake Balaton sensitivity to climate change and its impacts the problem came to the fore both for policy and science.

Fig. 2. Black Sea catchment.

Lake Balaton’s internationally unique vulnerability situation is the combined result mainly of its very shallow profile and the fact that through heavy reliance on tourism as a primary source of livelihoods, the socio-economic consequences of ecological deterioration can be severe and immediate. This is particularly the case as society has not fully dealt with the legacy of transition from centrally planned to a market economy. If the frequency of years with negative water balance indeed increased in the future, as indicated by applicable climate change scenarios, Lake Balaton and the coupled socio-economic system is expected to emerge as a highly sensitive and internationally unique indicator of vulnerability to global change. On a more positive side, it could also serve as a high profile example of adaptation measures consistent with sustainable development.

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6 Beyond State of the Art

The Black Sea has a long history of observation systems with for instance the regional Black Sea Global Ocean Observing System (BS-GOOS) funded by UNESCO. Another early project was the Black Sea Ecosystem Processes and Forecasting / Operational Database Management System. The Project was started in 1998 between major marine research institutions in six Black Sea countries, with the support of NATO Science for Peace Sub-Programme. The European Commission funded in the fifth framework a project called Regional Capacity Building and Networking Programme to Upgrade Monitoring and Forecasting Activity in the Black Sea Basin (ARENA). Another recent European project is the Black Sea Scene that aims at establishing a network of organisations around the Black Sea to improve data exchange and use. Let us cite also here the SESAME project that is studying the impact of expected changes such as climate on both the Mediterranean and Black Sea. The UNDP, GEF and UNOPS co-funded the Black Sea Ecosystem Recovery Project (BSERP) that aimed at reinforcing the Black Sea Commission and the cooperation between the countries, as well as assessing the environmental status and trend of the Black Sea.

EnviroGRIDS is clearly going beyond the state of the art in the Black Sea region by adopting a catchment approach and by tackling several societal benefits areas together. By using the most powerful computer network of the world it is clearly showing the direction on how to analyse the increasing amount of global data made available throughout the planet. It is bringing crucial information on future scenarios of expected climate, demographic and land cover changes. Based on the outputs of these scenarios it is building geoprocessing services in key societal benefits areas that will be connected back to the GEOSS.

Main innovations are:

• Contribute to free publicly-funded data through interoperable databases and services

• Streamline data process from data warehouses, to scenarios, hydrological models, impacts assessments and finally to disseminations tools.

• Use gridded computer technology to store and analyse environment data

• “Gridify” the code of hydrological model calibration and validation

• Create regional scenarios of development in function of expected climate, land cover and demographic changes

• Provide an early warning system to inform the citizens and decision makers on environmental vulnerability and risks associated to selected Societal Benefit Areas

• Build capacities for data sharing around GEOSS, INSPIRE and GMES.

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However, enviroGRIDS will strive to reuse the development of tools and concepts made earlier as several partners were active in these different projects. EnviroGRIDS will rely also on a modern Spatial Data Infrastructure (SDI). The European Commission has recently launched a new directive on Infrastructure for Spatial Information (INSPIRE)[11]. Spatial data is indeed very heterogeneous in format and quality across the European community and urgent efforts are needed to organize and standardize spatial data to improve its interoperability. Several global initiatives have emerged in recent years, such as the ‘Global Monitoring for Environment and Security’ (GMES) that aims at bringing data and information providers and users together, to improve environmental and security-related information and make it available to decision makers. The Global Earth Observation System of Systems (GEOSS) is coordinating existing systems by supporting interoperability, information sharing, improving the understanding of user requirements, and data delivery.

The United Nations are also developing their own system of access to key environment information through a spatial data infrastructure (UNSDI). The concept of SDIs reside in “working smarter, not harder” by re-using data, technical capabilities, skills, intellectual effort and capital, through the sharing the costs of people, technology and infrastructure. SDIs rely on the development of policies, technologies, data, common standards, standard practices, protocols and specifications such as those of the Open GIS Consortium (OGC). The governing principles of SDI include:

• Data access and sharing through a decentralized coordination framework

• Interoperability and standardization of tools

• Portability

• Build once, use many times

• Continuity and sustainability

7 Capacity building

Trainings, awareness raising and capacity building will be structured around results from the FP6 project NaturNet-Redime, namely on technologies for sharing of heterogeneous knowledge’s trough a so called Uniform Resource Management (URM). The capacity building activities of enviroGRIDS will follow the GEO Capacity Building strategy [12]. GEO’s use of the term “capacity building” is based on the definition established at the 1992 United Nations Conference on Environment and Development (UNCED) which encompasses human, scientific, technological, organizational and institutional resources and capabilities. GEO focuses on three elements of clearest relevance to Earth observations: human, institutional and infrastructure capacity:

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• Human capacity building refers to the education and training of

individuals to be aware of, access, use and develop Earth observation data and products. EnviroGRIDS will organize face to face and virtual trainings in different regions and on several thematic and technical topics covered in the project.

• Institutional capacity building is focused on developing and fostering an environment for the use of Earth observations to enhance decision making. This will be obtained by working along the objectives of the Black Sea Commission and the International Commission of the Protection or the Danube River that are both partners in this project. This includes building policies, programs and organizational structures in governments and organizations aimed at enhancing the understanding of the value of Earth observation data and products.

• Infrastructure capacity building is related to the hardware, software and other technology required to access, use and develop Earth observation data and products for decision making. Most of the infrastructure that will be built in enviroGRIDS will be developed in collaboration with the two international commissions so that they will be able to continue using it after the end of the project.

8 Remote sensing

EnviroGRIDS will promote the use of passive (naturally emitting/reflecting radiation) and active (backscattering of sensor illumination) types of remote sensing. In a first guideline on remote sensing use within enviroGRIDS [13], a comprehensive description of the types of remote sensing satellites and sensors is given (such as LANDSAT, SPOT, EO-1, EOS, ERS, MERIS, AVHRR, SeaWiFS, ASTER, MODIS, Ikonos, QuickBird), with their spectral, spatial, and temporal specifications, what they can detect, and some examples of applications.

The extended introduction into general aspects of remote sensing sets the scene for the explanation of the role that remote sensing can play in serving the objectives of the enviroGRIDS project. One of the key uses of remotely sensed land cover and land use data is the Soil Water Assessment Tool (SWAT). Another class of baseline data source for hydrological modelling are Digital Elevation Models (DEM) of the land’s surface. Various resolution DEM products with global coverage include 30 meter resolution and publicly accessible product of the ASTER Global DEM project, released recently within the GEOSS framework; as well as the popular 90 meter near-global scale Shuttle Radar Topography Mission (SRTM) DEM. Remote sensing can provide many other elements of data feed for hydrological modelling and these are presented further in the document. These

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remote sensing datasets include soil moisture and meteorological data (rainfall, wind speed, evapotranspiration, humidity).

To demonstrate the usefulness of remote sensing in environmental and change detection applications, enviroGRIDS will utilize the range of geographical distribution and experience of project partner organizations to consider the representative spectrum of case studies covering the watershed processes, interfaced with coastal areas of the Black Sea. Themes to be covered in case studies include biodiversity and ecosystem protection, coastal erosion, land cover change and development pressures, and the climate change impacts. These and other case and demonstration studies will feed into illustrated and annotated products for the utilization and information of governmental agencies, non-governmental organizations, and the general public education, in order to raise environmental awareness in the Black Sea region.

EnviroGRIDS envisioned also the usage of the grid infrastructure for remote sensing applications, as well as the coordination and interoperability aspects with other ongoing efforts to construction grid-based digital repositories for remotely sensed data, such as the GENESI-DR and other partner projects.

9 Sensors

In another deliverable, enviroGRIDS analyses the state-of-the-art in sensor technologies, Wireless Sensor Network and Web Sensor [14]. It also analyses different solutions on how to integrate sensor measurements into grid-enabled Spatial Data Infrastructures (GSDI). The role of the sensors in the international observation systems such as GEOSS, GMES and INSPIRE is reviewed. GEOSS objective is the development and implementation of the future Earth observing systems, including satellite, airborne, and in-situ observations. GMES defines in situ observations as one of the pillars of its infrastructure (one of the two groups of Core services). In situ observation is therefore an essential part of GMES and GEOSS. However, in comparison with the remote sensing, in situ observations are not well integrated. For example in INSPIRE, in situ monitoring is not included. Although several FP6 and FP7 projects are dealing with in situ monitoring (e.g. SANY, Osiris, Winsoc, Genesis), one example of the integration of in situ monitoring with SDI is the Uniform Resource Management GeoPortal (URM), which is based on INSPIRE, GMES and GEOSS principles. The URM concept divides in situ observations into three relatively independent blocks: Sensor technologies including networks of wireless sensors, sensor measurement integration, and Sensor Web. The problem of current research in the field is that most projects target these three parts separately and until now there is a large integration gap at the low level of Sensor Web protocols.

One task in the enviroGRIDS project is dedicated to analysing the needs for sensor measurements, including the definition of the observed phenomena, the

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definition of the accuracy of measurement and the definition of the frequency of measurement. This task will test different approaches for integrating standards of observation sensors with wireless sensors network. It will further explore the development of hardware and software solution to plug sensors into SDI. It will pursue the implementation of Sensor Web Enablement (SWE) standards and their integration with SDI and grid technologies.

10 Interoperability

In a third guideline, enviroGRIDS explores how the goal of a “sharing spirit” can be achieved through interoperability, with the importance of promoting collaboration and cooperation among partners and data holders [15,16]. Good communication and good organization are fundamental for sharing not only data but also information, knowledge and capacities. In consequence, high priority must be given to the creation of a well understood and accepted governance structure in order to develop a clear strategy for the deployment of the infrastructure. This will allow partners to share the same vision and to feel a common sense of ownership of the future Black Sea Observation System. This will certainly create a spirit of commitment around the project and thus would greatly facilitate the endorsement of a Spatial Data Infrastructure and its related concepts.

As presented in this deliverable, sharing fosters the notion of re-use of data, but also re-use of technical capabilities and skills developed, highlighting the importance of capacity-building, the necessity to learn from others and to share also knowledge among the different partners of the project. If collaboration is achieved with the help of good communication and organization, the agreement on the use of new standards, the development of guidelines, good practices and policies will greatly enhance the “open and shared spirit”.

Finally, the key challenge of the enviroGRIDS project is to bridge the technological gap between the world of Spatial Data Infrastructure and grid computing infrastructure, creating a grid-enabled SDI.

With the ever increasing spatial and temporal resolution of geospatial data causing a tremendous increase in term of size of these data, we progressively reach the limits of the processing capacities of the traditional GIS/SDI technology. With the uptake of grid technology and the progressive deployment of large infrastructure project like the EGEE many more scientific domains and technology-related activities have access to sizable computing resources. However, several differences between OGC-compliant SDIs and Grid infrastructures exist concerning the description of services, their interfaces, their state, the way they implement security and the way they catalogue metadata. All these differences must be taken into account in order to extend the analytical capabilities of traditional SDIs. Internal and external participants to enviroGRIDS will act as key

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drivers and pioneers, to promote sharing of data supported by SDI initiatives and serving and receiving data to and from systems like INSPIRE and GEOSS.

11 Grid technology

In a last guideline on data storage on the grid, we consider the Geospatial Web Services and grid Platform as important technologies supporting the development of the enviroGRIDS infrastructure [17] (Figure 3). Geospatial platforms provide spatial data oriented on specialized services such as storing, management, processing, and visualization. Grid technology hides the complexity of underlying infrastructure, providing techniques for data management and security, as well as the abstraction mechanism needed to deal with heterogeneous resources. The Grid platform supports single sign-on to distributed resources, transfer of large datasets at high speed, setting up of virtual organizations, maintenance of information in central and distributed catalogues, and efficient resources management.

Fig. 3. EnviroGRIDS system architecture [17].

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The enviroGRIDS system will comply with Service Oriented Architecture providing secure and persistent services over the Grid, and as stateless services over the Web. Services encapsulate the basic functionality provided to user applications by both Grid and Geospatial interoperable infrastructures.

12 Conclusions

Through the combination of these activities, the enviroGRIDS consortium aims at improving data access, use and utility in the Black Sea catchment. It will significantly build local, national and regional capacity on Observation Systems in order to better exchange knowledge and information and guide the region towards more sustainable development. The challenge is not only to improve data access from global to regional databases, but also to allow processing large data sets (Figure 4).

Fig. 4. EnviroGRIDS focus is on data sharing and data processing.

Regional organizations, such as the Black Sea International Commission and the International Commission for the Protection of the Danube River, as well as countries will be able to take advantage of enviroGRIDS to analyze large environmental datasets in a harmonized way in order to support the

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conceptualization and implementation of environmental and relevant sustainable development policies.

Acknowledgments. The authors wish to thank gratefully the European Commission for financing this project under FP7-ENV-2008-1 (grant agreement No. 226740).

References

1. PCU: Strategic Action Plan for the Danube River Basin 1995-2005 – Revision 1999. Danube Pollution Reduction Programme, Programme Co-ordination Unit. (1999)

2. GIWA: Global International Waters Assessment Eutrophication in the Black Sea region; Impact assessment and Causal chain analysis (2005)

3. IPCC: Climate Change 2007 - Impacts, Adaptation and Vulnerability - Contribution of Working Group II to the Fourth Assessment Report of the IPCC (2007a)

4. IPCC: Climate Change 2007 - Mitigation of Climate Change - Contribution of Working Group III to the Fourth Assessment Report of the IPCC (2007b)

5. IPCC: Climate Change 2007 - The Physical Science Basis - Contribution of Working Group I to the Fourth Assessment Report of the IPCC (2007c)

6. GWSP: The Global Water System Project: Science Framework and Implementation Activities. Earth System Science Partnership (2005)

7. CEC: Directive 2000/60/EC of the European Parliament and of the Council Establishing a Framework for the Community Action in the Field of Water Policy. Page 327 (2000)

8. Arnold, J.G., Srinivasan, R., Muttiah, R.S., Williams, J.R.: Large area hydrologic modeling and assessment part I: model development. Journal of American Water Resources Association 34 (1998) 73-89

9. Abbaspour, K.C., Yang J., Maximov I., Siber R., Bogner K, Mieleitner J., Zobrist J., Srinivasan R.: Spatially-distributed modelling of hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. Journal of Hydrology, 333 (2007) 413-430

10. IISD: Conceptual Framework for Integrated Vulnerability Assessment and Adaptation in the Lake Balaton Project. Winnipeg: IISD (2006)

11. CEC: Directive 2007/2/EC of the European Parliament and of the Council Establishing an Infrastructure for Spatial Information in the European Community (INSPIRE) Page 14 (2007)

12. GEO: GEO capacity building strategy (2007) 13. Allenbach K., Giuliani G., Lehmann A., Gvilava M., Bakuradze T., Bektas Balcik F.,

Goksel C., Sözen S.: EnviroGRIDS remote sensing data use and integration guideline. EnviroGRIDS Deliverable 2.4, p.90 (2009)

14. Charvat K., Jezek J., Musil M., Krivanek Z.: EnviroGRIDS interoperability guideline. EnviroGRIDS Deliverable 2.3, p.25. (2009)

15. Giuliani G., Ray N., Charvat K., Lehmann A.: EnviroGRIDS interoperability guideline. EnviroGRIDS Deliverable 2.1, p.92. (2009)

16. Giuliani G., Ray N., Schwarzer S., De Bono A., Peduzzi P., Dao H., Van Woerden J., Witt R., Beniston M., Lehmann A.: Sharing environmental data through GEOSS. International Journal of Applied Geospatial Research (2011)

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17. Gorgan D., Bacu V., Ray N. and Maier A.: EnviroGRIDS data storage guideline. EnviroGRIDS Deliverable 2.2, p.67. (2009)

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Emerging Infrastructures for managing Earth Science

Data: Experience at ESA

Roberto Cossu1 and Luigi Fusco1

1European Space Agency, Earth Observation Science, Applications and Future

Technologies Department {Roberto.Cossu, Luigi.Fusco}@esa.int

Abstract. A common dedicated infrastructure would permit the Earth Science communities to derive objective information and to share knowledge in all environmental sensitive domains over a continuum of time and a variety of geographical scales so addressing urgent and priority challenges such as Global Change. Federating data, information and knowledge for the management of our fragile planet is one of the major goals of the many international environmental programmes, eg GMES, GEO/GEOSS. In this chapter, we discuss, among other ESA participated project results, the achievements in the implementation of a collaboration platform for the federation and management of Earth Science Digital Repositories (GENESI-DR ‘Ground European Network for Earth Science Interoperations–Digital Repositories’ project). Such a dedicated community platform enables scientists to discover, locate, access, combine and integrate historical and fresh Earth-related data from space, airborne and in-situ sensors archived in large distributed repositories.

Keywords: Digital Earth, Earth Observation, Earth Science, Data Discovery, Data Access, Grid, OpenSearch, OGC, GEOSS.

1 Introduction

Digital Earth is a visionary concept for the virtual representation of the Earth that is spatially referenced, interconnected with the world’s digital knowledge archives, and encompassing all its systems and forms, including Earth Sciences, operational Natural Resources Management and Environmental Monitoring [1]. Several initiatives in ESA aim to fully realise that vision by enabling and supporting the interconnection and integration of the relevant digital and human knowledge across relevant stakeholder communities. They take full advantage, in the present digital age society, of the advancement in emerging technologies (space, instrumentation, ICT) to ensure the monitoring and safeguarding of the Planet Earth, which is increasingly in danger due to the strong presence and impact of the human life. In fact, in response to alarming situation, the United

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Nations has supported environmental conventions attempt to define internationally agreed protocols (e.g. Kyoto, Biodiversity and Montreal) to limit and monitor the status of our endangered planet. The World Summit on Sustainable Development, Johannesburg 2002 (WSSD), highlighted the urgent need for coordinated observations relating to the state of the Earth. It established the ad hoc intergovernmental Group on Earth Observations (GEO ) [2], co-chaired by the European Commission, Japan, South Africa, and the United States, and tasked it with the development of an initial ten year Implementation Plan by February 2005. The GEOSS ten year Implementation Plan [19] establishes the intent, operating principles, and institutional frame for developing a world-wide federated infrastructure for integrating available data and information to provide responses to the GEO institutional and scientific community.

The European Commission (EC) and the European Space Agency (ESA) initiated, jointly supported by all ESA and EU member states, a parallel international initiative called Global Monitoring for Environment and Security (GMES) [3], which is now considered to be the European contribution to GEOSS. This initiative considers, beside the development of operational environmental services to meet the institutional needs, as well as the development of a new generation of dedicated Earth Observation (EO) satellites (the GMES Sentinels) which will be used for ensuring environmental monitoring operational services in the coming decades. Since the conception of GMES and GEOSS, a lot of progress has been made in the definition and experimentation of infrastructure components dedicated to respond to the very articulated requirements of the world-wide environmental community.

The International Society for Digital Earth (ISDE) [1] is a non-political, non-governmental and profit international organization, aiming at promoting international cooperation on the Digital Earth vision, and enabling the Digital Earth technology to play key roles inter alia, in economic and social sustainable development, environmental protection, disaster mitigation, natural resources conservation and improvement of human being's living standard.

The implementation of the Digital Earth (in the vision of GEOSS) needs data, tools and world-wide infrastructures to gather and share the data, services and processing resources for building Virtual Research Facilities, which will permit the Digital Earth Community to share and derive objective information and increase their knowledge in socio-economic and environmental sensitive domains over a continuum of time (from historical measurement to real time assessment to short and long term predictions) and a variety of geographical scales.

This global infrastructure needs to include access to historical data holdings and networks of sensors, broadband communications via ground and space, efficient, effective and distributed computing and storage resources to take care of and handle the scientific tools, methodologies, data, etc. Today, information about the Earth, its state, socio-economic indicators, relevant services, data availability,

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project results and applications is accessible only in a very scattered way through different EO mission operators, scientific institutes, service companies, data catalogues, etc. For example, if we refer to Remote Sensing missions, only a limited community, who already knows what to search for, is today in a position to collect, compile and thus exploit the necessary EO information.

In this chapter we present the current initiatives at ESA in using emerging infrastructures for managing Earth Science (ES) data. Special focus is given to the achievements in the implementation of a collaboration platform for the federation and management of Earth Science Digital Repositories (GENESI-DR ‘Ground European Network for Earth Science Interoperations–Digital Repositories’ project). Such a dedicated community platform enables scientists to discover, locate, access, combine and integrate historical and fresh Earth-related data from space, airborne and in-situ sensors archived in large distributed repositories. Section 2 overviews the Earth Science Challenges. Section 3 describes recent ESA initiatives on emerging infrastructures for managing ES data, with special focus on the GENESI-DR platform. Conclusions are drawn in Section 4.

2 Earth Science Challenges

Data play a central role in ES and are the basic input to any ES application, directly or indirectly as they validate the results. The data come from sensors on different platforms, satellite, plane, boat, balloon, buoy or mast, or located at ground on the land. The data are distributed in different locations according to their topic and volume. A data policy is associated to each set of data and the data policy may change as a function of time. Petabytes of already acquired data are presently underexploited (<10%), because to get the results in a reasonable time not enough computing resources, tools and algorithms are available. However, even if they were to be made available, an efficient infrastructure to handle and treat very large data sets is still missing. In order to facilitate the access to data, their processing and visualisation, the ES community has developed Portals i.e. Web interface that integrates mainly several standard and specific-ES Web services. In some cases the portal provides access to service-based Grid for high performance processing. Different aspects need to be considered: data cataloguing, data discovery, digital right management for data, data access, data interoperability, metadata schemas, metadata exchange, and ontologies. In addition to data access, the requirement for intensive calculation due to large number of files (e.g., Monte Carlo approach, or re-processing of long series of data) also exists. The requirements for re-processing have been strongly increased over the last ten years. The science community expects rapid adaptation to new requirements, fast implementation of new algorithms in routine processing chains, and even fast re-processing of entire archives with these new algorithms.

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Furthermore, the different ES community domains use specific existing methods, approaches and working practices for gathering, storing and exchanging data and information. A shared e-Infrastructure approach is aimed at facilitating the linking up of disparate community localized infrastructure. However, these same differences impose considerable constraints which impact the increased effectiveness generated by the shared e-Infrastructure approach.

A global ES infrastructure needs to include access to historical data holdings and networks of sensors, broadband communications via ground and space, efficient, effective and distributed computing and storage resources to take care of and handle the scientific tools, methodologies, data, etc.

While conducting their research, Earth scientists are often hindered by the unnecessary complexity in locating and accessing the right data, products, and other information needed to turn data into results and knowledge, e.g. interpretation of the available data. We can state that the process of identifying and accessing data is typically the most expensive in time and effort. Of the different causes of this, those most frequently reencountered relate to:

• The physical discontinuity of data. Data are often dispersed over different data centres and local archives distributed all over Europe and abroad. Inherent to this, the different policies applied (e.g. access, costs), the variety of interoperability, confidentiality, and search protocols as well as the diversity of data storage formats. To access a multitude of data storage systems, users need to know how and where to find them and need a good technical/system background to interface with individual systems. Furthermore, often only the metadata catalogues can be accessed online, while the data themselves have to be retrieved offline.

• The diversity of (meta) data formats. New data formats are being introduced daily, not only due to the individual needs of a multitude of data centres, but also due to advances in science and instrumentation (satellites and sensors) creating entirely new types of data for research.

• The large volume of data. The total quantity of information produced, exchanged and requested is enormous and is expected to grow exponentially during the next decades, even faster than it did before. This is partly the result of the revolution in computational capacity and connectivity and advances in hardware and software, which combined together, are expanding the quality and quantity of research data and are providing scientists with a much greater capacity for data gathering, analysis and dissemination [19]. The validation of Earth remote sensing satellite instrument data and the development of algorithms for performing the necessary calibration and geophysical parameters extraction often require a large amount of processing resources. Often it also requires highly interactive access to large amounts of data to

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improve the statistical significance of the process. The same is true when users need to perform data mining or fusion for specific applications.

• The unavailability of historic data. Scientists do not only work with ‘fresh’ data, they also use historic data, e.g. global change research over long time periods. Here, different problems can be distinguished. First, it is evident that often no metadata are defined, or no common metadata standards are being used, and auxiliary knowledge needed by scientists to understand and use the data is missing, e.g. associated support information in science and technical reports. Although the problem exists also for fresh data, it is exacerbated when using historic data. Metadata will be at the heart of every effort to preserve digital data in the next few decades. It will be used to create maintenance and migration programs and will provide information on collections for the purpose of orienting long-term preservation strategies and systems [24]. Second, there are insufficient preservation policies in place for accessing historical data. After longer periods of time new technologies may have been introduced, hardware and software been upgraded, formats may have changed, and systems replaced. For example, it is almost impossible today to read files stored on 8-inch floppy disks which were popular just 25 years ago. Vast amounts of digital information from just 25 years ago are lost for all practical purposes [16].

• The many different actors involved. Science is becoming increasingly international and interdisciplinary, resulting in an increased total number of different actors involved (not only human). For example, ESA currently serves directly many thousand of users in the Earth Observation domain, many of whom need to exchange data, information and knowledge.

In Europe, different initiatives are supported by the European Commission (EC), e.g. as part of their specific action on Research Infrastructures, which aims to promote the development of a fabric of research infrastructures of highest quality and performance, and their optimum use on a European scale to ensure that researchers have access to data, tools, and models they need.

The ESA Science and Application Department of Earth Observation Programmes Directorate at ESRIN is involved in different initiatives focusing, in particular, on the use of emerging technologies for data access, exploitation, user information services and long-term preservation. For example, [20] provides an overview of the use of Grid, Web services, and Digital Library technology for long-term EO data preservation. In the EO community all emerging technologies can play a major role: infrastructures based on high-speed networks could support data access and drastically speed-up the transfer of the enormous quantities of data; Grid middleware could support the management of distributed heterogeneous resources including storage, processing power and communication, offering the

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possibility to significantly improve data access and processing times; digital libraries could help users locating data via advanced data mining techniques and user profiling. A shared distributed infrastructure integrating data dissemination with generic processing facilities shall be considered a very valuable and cost-effective approach to support Earth Science data access and utilization.

Among other specific technologies which have had an important role in the ES community, Web services in particular have played a key role for a long time. Web services technologies have emerged as a de facto standard for integrating disparate applications and systems using open standards. One example of a very specialized ES Web service is the Web mapping implementation specification proposed by the OpenGIS Consortium [23]. Thanks to Web services, Internet has become a platform for delivering not only data but also, most importantly, services. After a Web service is deployed on a Web server and made discoverable in an online registry of services, other applications can discover and invoke the deployed service to build larger, more comprehensive services, which in turn deliver an application and a solution to a user. Web based technologies provide also an efficient approach for distributing scientific data, extending the distribution of scientific data from a traditional centralized approach to a more distributed model. Some Web services address catalogue services to help users to locate datasets they need or at least narrow the number of datasets of interest from a large collection. The catalogue contains metadata records describing the datasets. Web services provide the fundamental mechanism for discovery and client-server interaction and have become a widely accepted, standardized infrastructure on which to build simple interactions. On the other hand, Grids were originally motivated by the need to manage groups of machines for scientific computation. For these reasons, Web Services and Grids are somehow complementary and their combination results in Grid services (e.g. Open Grid Services Architecture). Note that there, in the very recent past, there is a convergence approach in the definition of the Web Processing Service, by the Open GIS Consortium and by the Global GRID Forum [22].

3 A dedicated ES e-collaboration platform

Based on the successful experience of Grid Processing on Demand (G-POD) [6], a number of initiatives have started in ESA to develop an ES e-collaboration platform that makes use of Grid and SOA technologies. In the following subsections, first we briefly describe G-POD and discuss the ES grid roadmap generated by the DEGREE project. Afterwards, we focus our attention on GENESI-DR, which will practically deploy an ES dedicated infrastructure providing reliable, easy, long-term access to Earth Science data via the Internet.

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3.1 Grid technology for data access and processing: ESA Grid-Processing on Demand

Following the participation to DATAGRID, the first large European Commission funded Grid project [10], the ESA Science and Application Department of Earth Observation Programmes Directorate at ESRIN has focused on the development of a dedicated Earth Science Grid infrastructure, under the name Earth Observation Grid Processing on-Demand, G-POD [6, 21]. Coupled with high-performance and sizeable computing resources managed by Grid technologies, G-POD provides the necessary flexibility for building a virtual environment that gives transparent, fast, and easy access to data, computing resources, and results. Using a dedicated Web interface, each application has access to a catalogue like the ESA Multi-mission User Interface System (MUIS) [11,17] and storage elements. It furthermore communicates with the underlying Grid middleware, which coordinates all the necessary steps to retrieve, process, and display the requested products selected from the large database of ESA. This makes G-POD an ideal environment for processing large amounts of data, developing services which require fast production and delivery of results, comparing approaches and fully validating algorithms. In particular the G-POD concept and technology solves the equations:

• Move processors close to the data in a flexible and controlled way, thus leave the data wherever they are archived, reduce dissemination costs and effort

• Resources can be shared (data, tools, computing resources), thus reducing investments and running costs and reducing data flows to the minimum, with clear reliability and performance improvements.

A number of selected ESA Earth Observation missions and related software tools have been integrated by ESA into G-POD to provide for facilitating data handling and analysis. G-POD is nowadays used for global scale product generation, research activities, rapid mapping and so on. Some applications exploit the Grid technology for bulk processing of huge amount of products allowing e.g. the user to obtain large-scale high-resolution mosaics of EO data, other to provide fast access to large volumes of data. It is important to note the wide diversity of EO application themes, such as: meteorology, chemistry of the atmosphere, oceanography, simulations, operational generation of Level 3 products, generation of different products relevant to Essential Climate Variables (ECVs) [12] defined by GCOS, and production of maps for fast damage assessment. Methodologies for the analysis of multi-source data, time series, and data assimilation are being considered. Figure 1 shows some examples of MERIS Level-3 products generated in near real time in G-POD. ESA has recently offered scientists with the possibility to perform bulk processing and/or validation of their own algorithms exploiting this environment.

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In the following subsections, we details two G-POD applications, i.e., mosaicking of ASAR product for Arctic ice monitoring, and algal bloom monitoring.

Fig. 1. Examples of MERIS Level-3 products generated in near real time in G-POD.

The monitoring of the Arctic ice. On September 2007, the following news was published on ESA web site: “the area covered by sea ice in the Arctic has shrunk to its lowest level this week since satellite measurements began nearly 30 years ago, opening up the Northwest Passage – a long-sought short cut between Europe and Asia that has been historically impassable” [9]. The news had a world wide echo.

The study showed several mosaics (see Figure 2) Each mosaic was created from nearly 200 images acquired by the Advanced Synthetic Aperture Radar (ASAR) instrument aboard ESA’s Envisat satellite. All the mosaics were generated in G-POD environment.

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Fig. 2. Radar mosaics of the Arctic region related to the early September of 2005, 2006,

and 2007. The mosaics have been generated in G-POD and show the shrinking of the Arctic ice coverage.

On August 2008, ESA web news reported that “following last summer's record minimum ice cover in the Arctic, current observations from ESA's Envisat satellite suggest that the extent of polar sea-ice may again shrink to a level very close to that of last year” [7].

Also in this case a series of mosaics of the Arctic Ocean created from images acquired from the Advanced Synthetic Aperture Radar (ASAR) instrument aboard Envisat were made public (see Figure 3).

a) b)

c) d)

Fig. 3. Radar mosaics of the Arctic region related to the early June (a), July (b), August (c), and September (d) 2008. The mosaics have been generated in G-POD.

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Sargassum from space. On June 2007, the following news was published on ESA web site: “Envisat captures first image of Sargassum from space. Sargassum seaweed, famous in nautical lore for entangling ships in its dense floating vegetation, has been detected from space for the first time thanks to an instrument aboard ESA’s environmental satellite, Envisat. The ability to monitor Sargassum globally will allow researchers to understand better the primary productivity of the ocean and better predict climate change.” [8]. Using optical radiance data from the Medium Resolution Imaging Spectrometer (MERIS) aboard Envisat, Dr Jim Gower and Stephanie King of the Canadian Institute of Ocean Sciences and Dr Chuamin Hu of the US University of South Florida were able to identify extensive lines of floating Sargassum in the western Gulf of Mexico in the summer of 2005 (see Figure 4).

Fig. 4. Sargassum as seen from Envisat. The MERIS data processing has been performed

on G-POD.

The discovery was made using the MERIS maximum chlorophyll index (MCI) which provides an assessment of the amount of chlorophyll in vegetation to

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produce detailed images of chlorophyll per unit area. Gower and King combined data from MERIS with a sophisticated processing algorithm integrated in G-POD.

By using Grid technology, Gower and King intend to compute 5-years worth of MERIS data to determine global estimates of Sargassum biomass and its contribution to ocean productivity. "So far, we have found two things (Sargassum and Antarctic superblooms) that have never been seen from space before," said King. "It is really very exciting."

3.2 DEGREE

The Dissemination and Exploitation of GRids in Earth sciencE (DEGREE) project [4, 5] was a Specific Support Action, funded within the Grid call of EC FP6. The project aimed to promote the Grid culture within the different areas of ES and to widen the use of Grid infrastructure as platform for e-collaboration in the science and industrial sectors and for selected thematic areas which may immediately benefit from it. The DEGREE project was also tackling certain aspects presently considered as barriers to the widespread uptake of the technology, such as perceived complexity of the middleware and insufficient support for certain required functionality.

DEGREE had among its objectives the generation of a roadmap setting out the key steps needed for the ES community to move towards achieving its Grid objectives. These are believed to play a fundamental role to achieve some of the big challenges that ES is nowadays facing as data archiving and preservation, data access, data harmonization. A short discussion on the generated roadmap is given in the following subsection.

The roadmap. An ES Grid development roadmap was missing and its definition was of the main objectives of DEGREE. It is worth reminding that Grid is intended not as a goal but as a means for reaching the ES priorities. DEGREE partners believe that “Grid is a commodity ES users can benefit from to pursue their challenging objectives”. The major objectives of the roadmap were set out as a journey progressing through a list of objectives to be achieved in order to arrive at the final overall objective, i.e. the establishment of a well-identified ES Grid Platform. Various aspects were considered such as existing infrastructure, middleware, network and bandwidth, experiences gained within the EGEE project, etc. The result is a list of points arranged by category, specifying for each of them the expected achievements and the time period, from short-term to medium-term to long-term. The roadmap, which is in line the expected achievements of the major ES communities programmes/initiatives, like GEOSS [15] , SEIS [26], and INSPIRE [18], is publicly available at [1]. In the following we summarize the main points of the roadmap. One of the major objectives to be addressed in the short term is community building. Community building has a large governance component. For a Grid to achieve efficiency of scale, many organizations must

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participate (by installing Grid nodes, Grid access middleware, tools, datasets, etc.), yet without legislation and directives this will probably not happen. For this reason we urge the key actors at the political level (e.g. WMO, CEOS, GEO, space agency, IUGG, EGU) to engage in a lasting dialogue aimed at addressing the key issues raised by this roadmap. In parallel to building support to education, development of Grid training programmes are needed. A big effort should also be devoted in supporting large science community (as in G-POD). This includes single sign-on authentication to all ES data providers and implementing rules and methods for authorization to access restricted data (support for user roles, directory service, etc.). An additional major issue to be addressed in the short term is the definition and implementation of a standard approach to distributed data and metadata. The medium-term period is mainly oriented at solving outstanding blocking issues for ES applications deployment on Grid; porting of applications from different ES disciplines throughout a wide community; and facilitating access for everyday ES users to Grid. Other actions needed are: the integration, in Grid environment, of a lot more specific data handling tools. Data retrieve, reprocessing and systematic data processing shall be standard services in Grid; the direct deployment to the Grid storage of the most used very large environmental databases and file repositories (e.g., space and weather archives, climate reanalysis, seismic profiles, catalogues and waveforms); the integration of all the features needed for e-Collaboration among ES; the increased development of dedicated ES Grid tools base on standards and re-use; The consolidation of results from many ongoing projects and initiatives to concentrate the efforts in the creation of a common ES platform. The long-term objectives are fundamental for a real exploitation of grids in ES. Nonetheless, they will probably not be achieved unless medium term objectives are achieved. The effort required for achieving these objectives is more about end user engagement, than it is about the deployment of any particular technology. Thus, particular emphasis should be given to: ease of adoption; ease of use; hiding complexity from the end-user; understanding and supporting the "usual way of business" for ES end-users (do not force users to learn "arcane" computer knowledge or work in a fundamentally different way then they are used to). More details and discussion on the roadmap can be found in [1].

3.3 GE�ESI-DR

Ground European Network for Earth Science Interoperations - Digital Repositories (GENESI-DR) [14], an ESA-led, European Commission (EC)-funded two-year project, kicked-off early 2008 and is taking the lead in providing reliable, easy, long-term access to Earth Science data via the Internet. Petabytes of data about our planet are available but distributed at different locations. Currently, information about the state of the Earth, relevant services, analysis results, applications and tools are accessible in a very scattered and uncoordinated way,

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often through individual initiatives from Earth Observation mission operators, scientific institutes dealing with ground measurements, service companies, data catalogues, etc. Data access is a major logistic problem. The EC has funded GENESI-DR as a flagship project in Europe to help meet the challenge of facilitating life of scientists from different Earth Science disciplines located across Europe in discovery, access and use (combining, integrating, processing, …) of historical and fresh Earth-related data from space, airborne and in-situ sensors archived in large distributed repositories.

GENESI-DR is a response to the need for science users to be provided with data and tools to access, combine, and integrate the Earth-related data for performing their analyses.

GENESI-DR has the following very challenging objectives:

• To provide a base for (establishing) a world-wide e-infrastructure for Earth Science with European leadership

• To provide guaranteed, reliable, easy, effective, and operational access to a variety of data sources, and demonstrate how the same approach can be extended to provide access to all Earth Science data

• To harmonise operations at key Earth Science data repositories limiting fragmentation of solutions

• To demonstrate effective curation and prepare the frame for approaching long term preservation of Earth Science data

• To validate the effective capabilities required to access distributed repositories for new communities, including education, and assess benefits and impacts

• To integrate new scientific and technological derived paradigms in operational infrastructures in responds to the latest Earth Science requirements

Earth Science Requirements and GE�ESI-DR Validation Applications – As discussed in Section 2, data access is a major logistic problem that removes resources and focus out of the ES Research. The main requirement from Earth scientists is the access to a dedicated Earth Science (ES) infrastructure providing:

• The capability to discover all these data from different European Earth Science Digital Repositories (DR) through the same interface in a transparent and homogeneous way;

• Easiness and speed of access to and use (combining, integrating, processing) of large volumes of coherently maintained distributed data in an effective and timely way;

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• High performance computing resources accessible through standardized interfaces;

• Processing services to be used on data of interest.

In the context of the GENESI-DR a requirement gathering and analysis activity has been carried out, which has confirmed the above mentioned priorities. To this end, the following applications from the various Earth Science (i.e. land, atmosphere and marine) domains have been analyzed (and in a second phase integrated in GENESI-DR platform):

3ear Real-Time (3RT) Orthorectification for Agricultural Crop Checking - Building on an existing JRC software solution, this Validation Application involves the use of high resolution and very high resolution orthorectified reference data and DEM to ortho-correct satellite data. The service benefits from GENESI-DR through access to data (high resolution imagery and DEMs) and processing power. A science user will be able to discover the NRO Validation Application as a Web service within GENESI-DR and will be able to combine data with the remote processing service to obtain the desired results. Once results are produced, the science user will be able to redirect them to any DR that can host the output of the service. As well as supporting the “Controls with Remote Sensing”(CwRS) monitoring programme of EC DG Agriculture, the NOR Validation Application has a wide potential user group including the Urban Area Mapping in Support of Emergency Response Validation Application (see below).

Urban Area Mapping in Support of Emergency Response. The result of in-house development at JRC ISFEREA, this Validation Application has developed a systematic methodology for the characterization of built-up area in large urban settings, with a view on understanding up to date population dynamics in global mega-cities. The system employs a texture-based built-up area delineation procedure that can be applied to high resolution imagery from optical (SPOT-4/5, IKONOS, QuickBird) and SAR (Radarsat-1, ENVISAT, TerraSAR, CosmoSkyMed) satellites. Principal stakeholders for the Urban Area Mapping service are: European Commission Directorates General concerned with External Aid, Emergency response; UN Organizations involvedin population monitoring (UNDP, UN Habitat, UNDKPO, UNOSAT).The key role of these applications is to validate the GENESI-DR infrastructure against their initial set of requirements (documented in detail during the first year) and associated validation and verification plans including precise scenarios and case.

GlobModel - The ultimate goal for the Earth System modelling and forecasting community is to provide environmental services to monitor, understand and predict conditions for the whole Earth System, including physical and

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biogeochemical aspects. This vision greatly extends the range of services available today in operational weather forecasting and offers the prospect of operational services, inter alia, for oceans, atmospheric chemistry and land cover on a variety of spatial scales and timescales. Such services will underpin environmental policy decisions and provide direct services for citizens, for example warning of hazardous environmental conditions. In this context, the GlobModel [13] Validation Application, led by the Data Assimilation Research Centre (DARC), University of Reading, has developed a demonstrator combining air quality, and ozone and UV forecasting model output with the measurements available from EO satellites.A novel attribute of the demonstration within GENESI-DR is the use of new data with a strong European involvement (Envisat SCIAMACHY / EOS Aura OMI) that have not been assimilated previously in combination. The purpose of the application is:

• To show that multi-instrument data integration outputs (analyses, forecasts) are valuable for scientific purposes

• To demonstrate that providing a bridge between the scientific and operational communities gives enhanced operational and science benefits

• To show the feasibility of the remote integration of distributed European resources using existing European Research Infrastructures

Using just the initial GENESI-DR infrastructure, the GlobModel application has validated both manual and programmatic (API) scenarios of access to data. Additionally, it has implemented a user interface to the infrastructure that is independent of the GENESI-DR portal (see Figure 5).

SeaData3et - The aim of this Validation Application is to demonstrate interoperability between two federated Digital Repository systems: GENESI-DR and SeaDataNet [25]. SeaDataNet is being developed in parallel to GENESI-DR with the objective of providing INSPIRE compliant services to help manage the marine environment through the conservation of data collected by hundreds of scientific institutions working in Europe and adjacent areas, and make these data available. SeaDataNet has federated open digital repositories to manage, access and share data, information, products and knowledge originating from oceanographic fleets, new automatic observation systems and space sensors. The SeaDataNet infrastructure links 40 national oceanographic data centres and marine data centres from 35 countries riparian to all European seas. The data centres manage large sets of marine and ocean data, originating from their own institutes and from other parties in their country, in a variety of data management systems and configurations. A major objective and challenge in SeaDataNet is to provide an integrated and harmonised overview and access to these data resources, using a distributed network approach (see Figure 6).

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Fig. 5. GlobModel Visualization and Validation Service interface. The client queries

GENESI-DR for discovering and accessing heterogeneous data i.e., GlobModel results and Satellite observations.

Fig. 6. SeaDataNet validation scenario results. The figure shows heterogeneous data discovered and retrieved from different DRs and results of on-demand processing.

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Land Data Assimilation - Demonstration of this application is being developed by NILU with GENESI-DR providing both remote access in input data and to transfer model outputs to Earth Science research partners. Data assimilation is a technique involving the synthesis of a range of observations from many sources, and with a variety of errors, into a numerical model of an evolving system, e.g., the atmosphere or the land. Variables such as Land Surface Temperature (LST) and soil moisture are important for understanding interactions between the land and the atmosphere, involving energy, carbon and water cycles. This, in turn, benefits Numerical Weather Prediction (NWP) and climate prediction by allowing a better use of Earth Observation (EO) data; better simulation of land/atmosphere processes and improved initial states for prediction at various temporal scales. Monitoring of the land surface is also becoming increasingly important for addressing climate change issues. The focus of the application is model-EO data fusion to forecast LST using a stand-alone system ported to NILU. A novel attribute of the demonstrator is the use of a state-of-the-art EnKF assimilation system. The purpose of the application is to show the feasibility of the remote integration of distributed European resources using existing European research infrastructures.

PHAVEOS - The Phenology And Vegetation EO Service is targeting a user community of academic, governmental and NGO researchers interested in ecosystem assessment, forestry and coastal productivity. PHAVEOS aims to develop a range of products and tools which allow assessment of EO-derived phenology patterns, via a selection of biophysical parameter map time series. The space-derived vegetation parameter maps and phenology information is intended to compliment and extend users own in situ data and land cover mapping. PHAVEOS intends to use the computing resources federated in GENESI-DR for the production of vegetation maps and derived phenology products. Curation and dissemination of these products is also envisaged using the GENESI-DR system with further requirements for onward dissemination to the users. PHAVEOS has an initial exemplar set of users based around the United Kingdom: Forestry Commission; Joint Nature Conservation Committee; CEFAS is an internationally renowned aquatic scientific research and consultancy centre; Woodland Trust, the leading UK charity dedicated solely to the protection of native woodland heritage.

QUITSAT - This application is a project funded by the Italian Space Agency devoted to Air Quality (AQ) assessment through the fusion of observations coming from polar and geostationary satellite sensors and ground-based data collected by DOAS spectrometry, multispectral solar radiometry, lidar techniques and chemical transport modelling. The QUITSAT Pilot Project, aims to implement three subsystems for the main functionalities: Monitoring, Forecasting and Planning. Initially, the Monitoring sub-system, which provides measurements of the concentration at the ground of Particulate Matter, namely PM2.5, and gaseous pollutants (NO2, O3, SO2, HCHO) will be validating the GENESI-DR infrastructure. This will be done through generating estimates of PM2.5

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concentration at 10x10 km2 scale using MODIS data (the QM1 product). Stakeholders for this Validation Application are Environmental Agencies but also, in the future, Science/Research users.

SBAS - Interferometric Synthetic Aperture Radar (InSAR) involves combining two or more radar images of the same ground location in such a way that very precise measurements - down to a scale of a few millimeters - can be made of any ground motion taking place between image acquisitions. "Interferogram" images appear as rainbow-colored interference patterns. A complete set of colored bands, called "fringes", represents ground movement relative to the spacecraft of half a wavelength, which is 2.8 cm in the case of Envisat's ASAR. A Small BASeline (SBAS) algorithm, proposed by the scientists of Italy's Istituto per il Rilevamento Elettromagnetico dell' Ambiente (IREA-CNR), has been developed and integrated in GENESI-DR (see Figure 7). The same algorithm can be used either for analyzing long time-series to observe subsidence phenomena or to map rapid deformations e.g. after earthquakes (see Figure 8). The algorithm benefits from the GENESI-DR platform in i) easy discovery and access to SAR data, ii) transparent access to orbit files related to the SAR products and to iii) digital elevation model; and iv) transparent access to grid computer resource that allow a fast execution of the algorithm.

Fig. 7. The figure shows the web interface developed for the SBAS application.

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Fig. 8. The figure shows the interferogram obtained running the SBAS algorithm on the GENESI-DR platform and related to the earthquake that shook L’Aquila, Italy,

on April 6th 2009.

GE�ESI-DR architecture. GENESI-DR is responding to application requirements with the design and implementation of a multi-disciplinary platform, providing discovery capabilities of scattered and heterogeneous data (acquired by a multitude of sensors and related to different domains of Earth Science), providing easy and fast access to such data, processing services and computing resources on demand, making easier the dissemination of newly generated results. The GENESI-DR Service Oriented Architecture is realized by existing and newly developed services, interacting through SOAP and REST interfaces. These services are organized in five main layers as shown in Figure 9.

The Central Discovery Service provides the capability to discover and retrieve information regarding data collections and products existing in heterogeneous catalogues at federated DR sites. It identifies the DRs providing products fulfilling the user search criteria and returns the corresponding access points. As a next step, products complying with refined search criteria can be identified and the corresponding metadata are returned to the client which include the product access URL allowing product retrieval. Products never pass through the central site. Only a subset of metadata is stored in the central catalogue to make it possible the dataset series discovery and to allow GENESI-DR to automatically forward the

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refined user query towards the specific DRs. Metadata related to single data products are stored only at the DR owning the data.

Fig. 9. GENESI-DR layered architecture. Gray boxes are services that are already available. White boxes are services that will be considered during the second year.

Flexibility and performance are taken into consideration by making use of different and efficient data transfer technologies such as HTTPS, GridFTP, BitTorrent grouped in metalinks and of specialized geospatial data access services (e.g. the OGC WFS, WCS, and WMS, OPeNDAP). The GENESI-DR architecture provides the DR owners with a mechanism (Catalogue Generator) to produce a metadata catalogue by simply harvesting metadata from their storage systems. The Central Discovery Service communicates with the different DR catalogues through a web service gateway. This provides DR owners the capability to easily make available their data and URLs to a significantly increased audience with no need to duplicate them in a different storage system.

The architecture also embeds services to enable expert users exploiting computational and network resources in order to produce the final desired product. At present, this means passing input data to a processing service (e.g. a Grid Service or an OGC Web Processing Service) available at some sites.

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Deployment and validation. An initial set-up and deployment was performed during the first project year. As of today, 12 different Digital Repositories hosting more than 50 dataset series are integrated as visualised in Figure 10.

Series are heterogeneous and include satellite data, in situ data, images acquired by airborne sensors, digital elevation models and model outputs. Some of the integrated DRs are external to the GENESI-DR partnership and have been taken on board thanks to the collaboration with other projects/centers, e.g., the EGEE-III NA4 Earth Science cluster. For the integration of DRs a Minimum Requirements and GENESI-fication guide has been prepared for DR-owners to ease the integration of their already existing or new DRs.

Fig. 10. DRs federated in GENESI-DR as of November 2009

The GENESI-DR operational platform is currently being validated against the previously listed applications. Validation scenarios currently being tested include data discovery via Web Portal, data discovery via API, data access, multiple files downloading, data processing, processing of heterogeneous data products, registration of new results in GENESI-DR (so to make them discoverable to other users). As an example, the SeaDataNet scenario includes discovery via Web portal of heterogeneous data (satellite, in situ, maps), download of data, discovery of and access to processing services (on-demand generation of Sea Surface temperature maps from satellite data) (see Fig. 5).

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Research activities. Fast data access and preservation/curation of data are the principal areas of research in GENESI-DR. For the first, peer-to-peer technologies (e.g. BitTorrent and DeStore) have been analysed and are already represented/integrated in the architecture definition. Analysis and experimentation have also been started on additional areas of interests (e.g. security, OGC web services, protocols for partial access to data etc.) identified by means of a dedicated survey conducted at the start of the research activity.

As regards preservation and curation of data, GENESI-DR is analysing common approaches to preserve the historical archives to guarantee future access to these and derived information even if both software and hardware transformations may have occurred. Ensuring access to Earth Science data for future generations is of utmost importance because it allows for the continuity of knowledge generation improvement. For instance, and in 50 years from now, scientists accessing the climate change data of the then past 50 years will be able to better understand and detect trends in global warming and apply this knowledge to ongoing phenomena. During the first project period this research activity has defined a strategy for data curation to be employed in GENESI-DR and tools for supporting this strategy have been identified and are being subjected to architectural design and prototyping. GENESI-DR has started a strong cooperation with the EC-funded CASPAR project in the context of this activity.

Standardisation and dissemination activities. GENESI-DR works towards harmonising operations and applying approved standards, policies and interfaces at key Earth Science data repositories. To support this undertaking, GENESI-DR is establishing links with relevant organisations and programmes such as space agencies, institutional environmental programmes, international Earth Science programmes and standardisation bodies. The project is considering and adopting, ISO 19115, ISO 19139 and OGC standards for geospatial metadata and processing (WPS), is compliant with the basis of emerging INSPIRE Implementing Rules for Metadata and Discovery, and is using OpenSearch protocol with Geo extensions for data and services discovery. Partners in GENESI-DR are involved in the INSPIRE Metadata and Discovery Services Drafting activity since its beginning, submitting comments in consultation periods through the FOSS SDIC at the Open Source Geospatial Foundation, and providing feedback on the Dublin Core implementation guidelines directly to JRC. Moreover, GENESI-DR is preparing an OGC discussion paper on the approach taken to metadata discovery using the OpenSearch Geospatial Extensions and adding in extension vocabulary specific to an application domain - in our case the properties of Earth Science data products.

GENESI-DR is increasing its involvement with OGC and taking advantage of the forum to promote a "Mass Market" approach to geospatial metadata and search services which is complementary to the CSW2 ISO19139 Application Profile, and

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maintains to the fullest extent possible compliance with the INSPIRE Implementing Rules. GENESI-DR’s OpenSearch Geospatial Extensions OGC Discussion Document (09-084) discussion paper is now approved for release in a Mass Market Geo DWG motion.

GENESI-DR has also liaised with various projects and interfaces have been defined to make optimal access to GENESI-DR components/services. In particular the following interfaces with external projects are noted: EGEE-III NA4 Earth Science Cluster (for testing discover, access, WPS call, processing); METAFOR (metadata standard description); SeaDataNet (format conversion, visualisation) SEE-GRID. An important activity GENESI-DR supports is the GEO/GEOSS initiative by contributing to the DA-09-02a GEO task for effective management of large volumes and diverse types of Earth Observation data.

4 Discussion and Conclusions

After one year and a half of activity, GENESI-DR has set-up and deployed an operational platform which is aimed at offering Earth scientists reliable, easy, long-term access to Earth Science data via the Internet. In particular, the project has demonstrated viability of GENESI-DR solution for discovery, access and on demand processing of many sources of Earth Science data.

The achievements of GENESI-DR are tangible. A critical analysis of the present achievements highlights the following:

• All collaborations demonstrated the value of the federated approach and express interest in GENESI-DR infrastructure to be evolved and moved in operations. In particular, some projects consider now GENESI-DR as their primary access point to ES data

• GENESI-DR is extendible to the wide and multidisciplinary Earth Science user communities, including research, related institutional, industry & operational actors; collaborations have demonstrated how the infrastructure can be adopted even for socio-economic studies.

• Communities still need customised services in their specific community environment while sharing data for collaboration. Each community has in fact its own tools, needs, habits, and it is necessary to make the core and essential GENESI-DR services (like data discovery, access and on demand processing) customisable as much as possible on these driving factors.

Acknowledgments. Ground European Network for Earth Science Interoperations - Digital Repositories (GENESI-DR) (http://www.genesi-dr.eu/) is a project, co-funded by the European Community's Seventh Framework Programme FP7/2007-

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2013 under grant agreement n° 212073 addressing work programme topic INFRA-2007-1.2.1: Scientific Digital Repositories and implemented by a consortium led by the European Space Agency, aimed at providing reliable, easy, long-term access to Earth Science data via the Internet. The project kicked off on the first of January 2008 and its duration is two years. The contact person is Luigi Fusco ([email protected]).

References

1. International Society for Digital Earth - http://www.digitalearth-isde.org/ 2. The Global Earth Observation System of Systems (GEOSS)10-Year Implementation

Plan: http://www.earthobservations.org/documents/10-Year%20Implementation%20Plan.pdf

3. Global Monitoring for Environment and Security: http://www.gmes.info 4. DEGREE – Earth Science white paper on Grids: https://www.eu-

degree.eu/DEGREE/internal-section/wp6/DEGREE-D6.1.2_v2.8.pdf/view 5. Dissemination and Exploitation of Grid foe Earth sciencE (DEGREE) website:

http://www.eu-degree.eu 6. ESA Grid Processing on-Demand (G-POD) Web portal: http://eogrid.esrin.esa.int. 7. ESA web news: Arctic ice on the verge of another all-time low,

http://www.esa.int/esaEO/SEMCKX0SAKF_index_0.html 8. ESA web news: Envisat captures first image of Sargassum from space

http://www.esa.int/esaCP/SEMHO6ARR1F_index_0.html 9. ESA web news: Satellites witness lowest Arctic ice coverage in history,

http://www.esa.int/esaEO/SEMYTC13J6F_index_0.html 10. European Data Grid Project website: http://www.eu-datagrid.org. 11. G. Landgraf and L.Fusco, “Earthnet online — The ESA Earth Observation Multi-

Mission User Information Services” ESA bulletin 93, February 1998, 12. Global Climate Observing System (GCOS) website:

http://www.wmo.int/pages/prog/gcos/ 13. GlobModel project website: http://www.globmodel.info 14. Ground European Network for Earth Science Interoperations - Digital Repositories

(GENESI-DR) website: http://www.genesi-dr.eu/ 15. Group on Earth Observations website: http://www.earthobservations.org/ 16. H. Besser (1999): Digital Longevity, Chapter in Maxine Sitts (ed.) Handbook for

Digital Projects: A Management Tool for Preservation and Access, Andover MA: Northeast Document Conservation Center, 2000, pages 155 – 166.

17. http://www.esa.int/esapub/bulletin/bullet93/LANDGRAF.pdf 18. INSPIRE website : http://www.ec-gis.org/inspire 19. International Council for Science (2004): Report of the CSPR Assessment Panel on

scientific Data and Information, December 2004, ISBN 0-930357-60-4. 20. L. Fusco, and J. van Bemmelen, (2004): Earth Observation Archives in Digital Library

and Grid Infrastructures, Data Science Journal, Volume 3, pages 222 - 226, 30 December 2004.

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21. L.Fusco, R.Cossu, C.Retscher, “Open Grid services for Envisat and Earth observation applications” in High Performance Computing in Remote Sensing, Ed: Antonio Plaza, Taylor and Francis Group, Chapter 13.

22. Open Grid Forum 22 website: http://www.ogf.org/OGF22/ 23. OpenGIS website: http://www.opengis.org. 24. P. Gauthier, et al (2003): Ensuring the sustainability of online Cultural and Heritage

Content: From an Economic Model to an Adapted Strategy, M2W FIAM - 2003. 25. SeaDataNet website: http://www.seadatanet.org/ 26. Shared Environmental Information System (SEIS) website:

http://ec.europa.eu/environment/seis/index.htm

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A novel approach to Environmental Monitoring System

for Landslides and Fire detection

¹Paolo Capodieci- Selex Communications S.p.a, WINSOC Project Coordinator

²Fabio Mengoni- Selex Communications S.p.a, Project Designer

¹Selex Communications, via dell'Industria 4, 00040 Pomezia (Rome, Italy) [email protected]

²Selex Communications, via dell'Industria 4, 00040 Pomezia (Rome, Italy) [email protected]

Abstract. Sensor networks are currently receiving a considerable attention as a basic tool to detect events or monitor physical parameters for emergency or hazardous situations, like radiation, pollution, temperatures, pressures, and so on. One of the main problems in designing sensor networks is on one side, the high reliability required to the whole system and, on the other side, the potential unreliability of the single node. This paper describes the scope and the results reached with the project WINSOC. The project has been funded by the European Commission under FP6 Framework. In Winsoc has been developed a totally innovative design methodology where the high accuracy and reliability of the whole network is achieved by introducing a suitable coupling among adjacent, low cost, sensors, enabling a global distributed detection or estimation more accurate than that achievable by each single sensor, without the need for sending all the data to a fusion centre.

Keywords: WSN, Wireless Sensor Node, wireless ad-hoc network, Environmental monitoring, mobile ad hoc network (MANET), Natural Hazards, Wildfires.

1 Why WS�

The opportunities for WSNs appear clearly in substituting the wired infrastructures for sensing (around 99% of sensors installed in the world are still wired); this substitution will allow reducing costs and improving flexibility, and also in creating new paradigms/opportunities for sensing where wiring is not possible. As a matter of fact and as an illustrative example, within the process industry, the installation of wireless monitoring equipment is one-tenth the cost of wired technology

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WSN technology beats the wired alternative in terms of technical/operational advantages: around 90% reduction in cost, even at current prices, and very often WSN enables things to be done that are otherwise impossible.

However, the interest in WSN technology and in the broad field of Ubiquitous Computing (where WSN is embedded) continues growing: there is a clear increasing excitement in the scientific community. The research activity is augmenting — more efforts and also more funding are characterizing the present WSNs research landscape and the future looks bright.

The massive funding is viewed as an important driver ─ the consultancy firm On World recently released figures projecting R&D spending on WSNs to reach $1.3 billion in 2012, up from $522 million in 2007

The conclusion is that both, the promise of the technology and the size of the applications domain continue growing.

2 Application field

Presently, WSNs typically measure physical variables as pressure, temperature, pH, humidity, light, gases/liquids, real-time location, cracks, vibration, shock, wind speed and direction.

Applications within environmental sustainability are large and varied: precision agriculture, coral reefs, lakes, space, wildfires, landslides are some of them. In particular, agriculture appears as the most promising in terms of business ─ WSNs help in precision irrigation, pesticide treatment, and harvesting so a reduction in environment damage can be achieved as decreasing the release of harmful chemicals and reducing the consumption of scarce energy; thus diminishing operational costs while increasing crop quality.

Environmental sensors connected to global information systems is one of the Selected Notes from the Millennium Project´s 2007 State of the Future Report. Also, as a consequence of the many natural disasters that took place during 2005, public focus is shifting from artificial blunders to natural calamities, thus creating considerable potential for smart sensors in environment monitoring systems.

In terms of applications domains there are a huge filed of application. Hereafter will be mentioned those relevant for Environment monitoring:

• Environmental sustainability. Environmental sustainability can benefit from WSNs, by using them for monitoring purposes with the goal to protect valuable resources from overuse or damage, as well as for maintenance purposes, that is, being able to continuously collect valuable information previously considered too difficult and too costly. Also, within the associated area of emergencies and early warnings, WSNs allow to gather accurate and reliable information enabling early warnings

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and rapid coordinated responses to potential threats. This encompasses the ability to enhance national security from hostile threats as well as the ability to save lives and economic losses associated to structural damages (buildings, pipelines, water utilities, and the like) through environmental monitoring of natural disasters. Within this broad field of environment, ecology appears as an important absorber of WSNs technology since ecology needs continuously monitoring a lot of variables; this is an area where experimental WSNs work is increasing.

• Water quality: monitoring and inspection system for pipes and pipe networks in water and wastewater. Water infrastructures are viewed as an important field the within critical infrastructures scenario.

• Radiation detection. This application concerns security matters since provides defense against the potential detonation of a radiological dispersion device capable of broadcasting non-fissile but highly radioactive particles over densely populated areas.

• Agriculture. Precision agriculture. The agricultural sector is undoubtedly a critical source of income and production worldwide. Furthermore, agriculture is strongly related to sustainability matters ─ water and soil conservation fundamentally. The efficient use of these resources through ICT continuous monitoring is crucial to reduce costs while maintaining performance. The problem in agriculture is that the environment/scenario is highly dynamic, big quantities of data are needed, and continuous attention/measurements are required: so pervasive computing technologies are perfect to solve the problem. Concerning soil & crops condition monitoring, WSNs can be used to monitor temperature, humidity, fertiliser and pesticide levels; in this way pesticide and fertiliser are applied only when needed and this implies strongly reducing costs – as an example, eliminating only one unnecessary treatment in 100,000 acres can originate a reduction of 2 million Euro given that a pesticide/fertilizer for one acre is 20 Euro.

• Farming: in the milking arena for example, WSNs can applied to the cow, milking equipment and feeding points to monitor quality, illness, right periods for insemination.

• Manufacturing/process control/control engineering. Continuous monitoring of processes, plant and machinery provides valuable data about the performance and condition of that equipment and machinery. This data can then be used to optimise the operation and availability of plant, improve cost-efficiency of maintenance work, prevent accidents and make significant savings in energy costs.

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2.1 The importance of landslides detection

Landslide, floods, drought, wildfire, storms, tsunami, earthquakes and other types of natural hazards are increasingly affecting the world. In the decade 1996-2005 disasters affected 3 billion people, killed over 750000 people and cost around US$600 billion according to OFDA/CRED. The Governments are conscious that it is not possible to let this trend continue. An example of actions in this strand is the Hyogo Framework Action (HFA) that represents one of the most comprehensive action-oriented policy guidance in understanding of disasters induced by vulnerability to natural hazards. Landslides in particular constitute an important issue to tackle within natural disasters ─ they pose considerable risks to humans and cause important disruption and economic losses when they affect infrastructures as roads, gates, and utility lines.

There is an increasing concern of the different Administrations about the necessity to face the problems of landslides: the International Consortium on Landslides and the International Programme on Landslides are some of them; a complete list of entities is provided in the final part of this report. Both initiatives encompass research, education, and capacity-building in landslide risk reduction, are participated and receive support from international, governmental and non-governmental organizations and entities (UNESCO, WMO─World Metereological Organization, FAO, UN/ISDR), and contribute to the International Strategy for Disaster Reduction (ISDR) and to the implementation of the Hyogo Framework.

Fig. 1. Sensors Column and Communica-tion Node for Landslide application

ICL and IPL have established a UNITWIN Cooperation Programme on Landslide Risk Mitigation for Society and the Environment in the framework of the UNITWIN/UNESCO Chairs Programme, at Kyoto University. Enhancement of

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early warning as well as preparedness and landslide risk management have been expressed as priorities within HFA.

2.2 The importance of fire detection

Forest fires have been identified as one of the most important threats to forests in Europe, especially in the Mediterranean region. Policy and management measures at different levels are being developed and implemented to minimize the negative economic and social impacts of forest fires. The implementation of such measures requires substantial investment of financial, human and organizational resources. In order to estimate whether investments in forest fire related measures (e.g. prevention) are justified, and to choose the optimal amongst several alternatives (i.e. the combination of investments in fire prevention, fire fighting and amount of wildfire), reliable data is needed on economic impact of forest fires and the economic efficiency of fire management measures. To improve the current situation and to provide useful and reliable information to decision makers, a standardised model for the assessment of economic impacts of forest fires and estimation of economic efficiency of fire management measures needs to be developed.

Fig. 2. Fire detection sensor node

Fires rank among the top causes of damage to Europe's forests. Every year forest fires burn, on average, about 500 000 hectares in Europe — twice the area of Luxembourg. About 95 % of the total area burnt lies in the Mediterranean region,

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with most damage occurring during the summer. Although the number of fires in the last decade has increased in Europe, the area burnt has not risen significantly due to improved fire fighting methods. In fact, disturbances such as naturally occurring forest fires are an element of the normal functioning of ecosystems. By creating open environments that return to forest over time, fires create a succession of habitats in which different organisms can thrive. Indeed, many species in both the Mediterranean and the northern (boreal) forests depend on such habitats. Paradoxically, in the boreal region fire control is extremely efficient and it has become necessary to carry out planned burnings to create habitats for several threatened fire-dependant species. The Mediterranean presents a different picture. The current fire frequency due to human activity is considered much larger than the natural rate. This constitutes a problem for human settlements and for ecosystem conditions and biodiversity. Excessively frequent fires degrade habitat quality and destroy ecosystems, including forests, which need time to develop. In addition to losing a part of their habitat, forest animals suffer from greater distances between fragmented forest patches. Less connectivity between small forest areas makes it more difficult for animals to ensure a viable gene pool and survive in the long term. Excessive forest fires also wipe out some of the services and benefits we obtain from forest ecosystems, including wood for buildings, paper and fuel, recreational services and food products. The environmental impact of forest fires is not limited to biodiversity and ecosystem services. They also result in emissions of particles and gases (including CO2) into the atmosphere, outflow of mineral nutrients, and destruction of the organic layer of the soil. Furthermore, they alter the water infiltration rates in the soil, making burnt areas more prone to erosion, soil loss and landslides. Excessive forest fires aggravate the extent of damage caused by such natural phenomena to critical levels. Recurrent fires when combined with droughts, especially in southern parts of Europe, may also lead to desertification.

During 2004, fires in these five countries burned a total area of 346 766 hectares, which is below the average for the last 25 years. Conversely, the number of fires that occurred (53 489) is above the average for the last 25 years

3 Winsoc general project objectives

WINSOC project pursued the development of sensor nodes based on the biologically inspired systems. Unlike the classical telecommunication network nodes, where complex protocol interactions are utilized for end-to-end communications, we designed “small” computing machines in the network. Such nodes need only the implementation of very simple rules. The inefficiency encountered by the current complex protocols will be overcome through the innovative resource control techniques proposed here. The uniqueness of the research has been to decentralize the decision-making process at the node level.

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The implementation of sensor networks involved methods allowing the devices to make decisions based on their local environment and their own individual state that would result in the global purpose of the network being fulfilled.

The network has been organized in two hierarchical levels. At the low level, there are very simple nodes gathering relevant information and interacting each other to achieve a consensus about the locally observed phenomenon. The interaction occurs through a very simple mechanism, not requiring complex modulation schemes, MAC, or routing strategies. This mutual interaction among the sensors (low level nodes) is a key feature, as it improves the reliability of the local decisions and, at the same time, it yields to fault tolerance and scalability. The low level nodes reach a value of consensus among their local measurements that makes possible to interrogate anyone of them to know this value; that is what upper level nodes do. The decisions that the upper level nodes extract from the low level nodes network (or cluster) is then forwarded to the appropriate control centers. Building on this fundamental structure, WINSOC had three primary objectives:

• Develop and test innovative algorithms implementing the self-organization capabilities of the low level sensors and devise the most appropriate radio interface responsible for the interaction among nearby sensors; this technology has a rather broad scope and it is especially useful for environmental monitoring

• Develop and test system level simulators addressing the following applications in environmental monitoring: i) detection or prediction of landslides; ii) monitoring of temperature fields, as a way to detect fires or to predict the potential risk of a fire in a given area. The simulators will incorporate the emulation of the physical environment, the reaction of the network to hazardous events, the performance of the network in terms of reaction time, probability of detection, estimation accuracy, localization, fault tolerance

• Develop a reduced scale experiment for testing the proposed approach in the case of temperature monitoring and obtain the deployment experience from landslide detection experiments with in-situ monitoring

These project objectives have been pursued by the fulfillment of the following specific targets:

System requirements Objectives

• Specification of services based sensor network applications and end-user requirements. This analysis examined with the description of sensor networks scenarios, services, and requirements. The purpose of the analysis was to provide designers of WINSOC system with a general understanding of users’ needs and behaviors, propose the description of

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sensor services and their wider integration with relevant web services, and specify the requirements on sensor system network and radio links.

• Requirements for the chip technology, transducers, radio links and the network deals with the description of required sensors component. The purpose of the analysis was to provide description of requested functionality and their comparison with COTS components. The analysis defined the WINSOC nodes development requirements.

Research Objectives

• Development of a novel, bio-inspired, paradigm for low complexity wireless sensor nodes, enabling self-organisation and distributed processing, without the need of sending all the gathered data to a sink node.

• The fundamental limits of wireless ad-hoc/sensor networks have been reviewed with a special focus to scaling laws describing the transport capacity as a function of the number of nodes. The hierarchical design methodologies followed by WINSOC have been detailed. The basic algorithms for achieving the appropriate decisions, either estimation or detection, using centralized or decentralized approaches have been reviewed; focus has been put on the cooperation algorithms, to be implemented on each node, leading to globally optimal decisions on each node, without the need to send all the data to a fusion centre. A mapping of algorithms into a real physical scenario (taking into account the impairments introduced by the propagation through a physical channel, like fading, delay, noise) has been carried-out. The strategies to be followed to build the network according to hierarchical structures were studied and implemented. The different network functionalities that can be implemented in a distributed fashion have been also analyzed. Activities have been devoted to the radio access techniques better suited at implementing the interaction mechanisms leading to the desired distributed decision.

• Investigation and evaluation of methodologies (passive, event-driven, on-demand) specifically designed for the extraction of the (punctual, clustered or global) information from the novel type of sensor network.

Technological Development Objectives

• Analysis of the candidate radio interface technologies and their suitability for the sensor node design.

• The focus of this activity has been on the analysis of sensor circuital design and radio access modulation schemes, constrained both to the requirements on transmitted power and to the achievement of the network

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performances, aimed at maximizing the network operational life and coping with possible restriction on EM emissions.

• The main requirements concerning the radio interface and the candidate protocols to the final design of radio access scheme are proposed, providing a comparison among them, as far as WINSOC main requirements is concerned.

• Performance evaluation of a system level simulator, integrating the whole network, showing the impact that the introduced underlying sensors coupling mechanism would have on the intended network service.

4 The Winsoc node

The WINSOC node is the “basic entity” of the final demonstration that will validate the profitability of the distributed mutual coupling algorithm for the Wireless Sensor Network context. In the following it is generally introduced the captions “Winsoc Algorithm” or “Winsoc Processing” referring to the above mentioned coupling mutual algorithm.

The node prototype (called WiNode) can be described as the combination of following entities (Figure 3):

• a set of sensors

• a microcontroller

• a radio transceiver Chipcon CC1100

• a battery power supply

• an antenna and an antenna front-end

The figure is rough illustration of the node prototype and particularly of the communication module; in the following the hardware aspects are described in details.

The network is organized in two hierarchical levels, indicated as L1 and L2 nodes for the sake of simplicity; their tasks have been previously described.

The L1 and L2 nodes are basically equal from hardware point of view. They have the same radio interface, the same microcontroller, the same antenna. L2 nodes are not equipped with sensors since they represent a sort of base station whose task is to extract information from the network composed of L1 nodes and provide it to the control center. The information extraction is easily achieved, considering that L2 nodes are part of the network (from a geographical point of view) and so they are able to listen to the transmissions of the L1 nodes and thus of the consensus value achieved by them.

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Fig. 3. WiNoDe overview

A Hardware view

The current section and sub-sections deal with the hardware features of the prototype node.

The single node interacts with the local sensor/s and with the other nodes belonging to the wireless sensor network.

The node’s hardware architecture is mainly composed of the following modules:

• 1 Communication Module (wireless motherboard)

• 1 I/O board (to develop a line driving)

• 1 Battery Package,

The following Figure 4 illustrates the hardware architecture in a sort of “object oriented” representation: a Wireless Motherboard which “uses” an I/O board, and a Power Supply Package.

Flash

Power

Connector

ISM

Radio

Transceiver

Micro Controller

Sensor

Antenna

Power Connector

Sensor/s

MICRO

CONTROLLER

CC1100

RADIO

TRANSCEIVER

RF FRONT END

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Fig. 4. Hardware architecture’s main modules

The Figure 5 and Figure 6 provide a full illustration of the WiNoDe

Fig. 5. WiNoDe complete scheme

I/O Board Wireless Motherboard uses

WIRELESS �ODE

1

1

Power Supply Package 1

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Fig. 6. 3-D image of the WiNoDe

The following picture (Figure 7) illustrates the main objects belonging to the Communication Module.

The single chip radio transceiver is the Chipcon CC1100 (working on unlicensed ISM bands, at different data rates up to 500 kbps, with different modulation techniques).

The Microcontroller shall be the LPC2138 (ARM7, 60 MHz, UARTs, SPI, SSP, Fast I2C-bus). The module has an external memory flash with serial access, whose minimum size is 128 Kbytes. The choice of the components is oriented to the minimization of their number and their size, compatibly with the technologies and the costs that they imply.

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Micro

Controller

Flash

Memory

Single Chip Radio

Transceiver

Antenna Front/End

Communication Module

To channel

Micro

Controller

Flash

Memory

Single Chip Radio

Transceiver

Antenna Front/End

Communication Module

Micro

Controller

Flash

Memory

Single Chip Radio

Transceiver

Antenna Front/End

Communication Module

To channel

Fig. 7. Functional Scheme Communication module

The I/O board makes available outward (for the acquisition from the sensor/s and for debug purposes) the serial interfaces RS-232 and RS-485.

The node is supplied by a voltage comprised between 3 and 3.6 Vdc by means of the Nickel-Metal Hybrid batteries (NiMH).

The node satisfies different environmental requirements (temperature, humidity, salty fog, rain, sand and dust; shock, fall and vibrations; electro-magnetic emissions) as the ones specified in many standards defined by ETSI, IEC and others.

Antenna’s aspects

A specific multi-band miniature antenna has been developed to be successfully integrated on the node sensor structure. Considering the main node antenna specifications given below, three main issues have been particularly studied: the miniaturization of the radiating structure, the multi-band operating mode and the antenna integration over the node chassis.

Antenna developments have been carried out using 3D electromagnetism simulation tool based on Finite Integral in Time Domain (CST MWS).

The form factor of the antenna is chosen to be similar to the node (parallelepipedic) for an easy integration. The antenna is located onto the top large side of the node and must be oriented horizontally for omni-directional radiation properties with vertical polarization. Dimensions of the antenna are chosen in accordance with node chassis structure and top metallic face of the box node will act as a ground plane for the antenna.

A view of the developed radiating structure onto the node enclosure is given in Figure 8. The antenna dimensions are compared to the operating lower wavelength (λ) to underline the miniaturization works.

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76 mm (λ/12.5)

10 mm (λ/90)

76 mm (λ/12.5) 2 hats

2 slots

2 shorting posts

feeding probe

air

dielectric substrate

node enclosure

Fig. 8. Developed antenna structure over node chassis

Specific optimization works, firstly made by simulations and done experimentally at a later time) are necessary to take into account key elements of the node structure from the antenna point of view (node chassis, RF connecting, cable, plastic housing).

Some preliminary results obtained from the electromagnetism simulation tool are given hereafter to illustrate the operating properties of the studied radiating structure. The reflection coefficient at the antenna input port is plotted in Figure 9. The operating frequency bands are shown in green. A good impedance matching (|S11| < -10 dB) is obtained around 315, 433 and 868 MHz. Slight improvements must be obtained at 915 MHz.

-30

-25

-20

-15

-10

-5

0

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2

|S11| (dB)

frequency (GHz)

Fig. 9. Reflection coefficient at the antenna input port

Far-field 3D gain patterns are presented in Figure 10 at different frequencies. This gain takes into account all the losses of the radiating structure, including possible

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impedance mismatching. Stable dipolar type radiation (omni-directional) is observable whatever the frequency. Gain and efficiency increase with frequency as predicted by physical laws. Unusual very low efficiency (gain) is observable at 315 MHz and new developments works are in progress to improve the radiation efficiency at this frequency.

F = 315 MHz

η= 2.5 %

F = 433 MHz

η = 14 %

F = 868 MHz

η = 67 %

dBi dBidBi

Fig. 10. 3D gain pattern at 3 operating frequencies

A software view

The WiNoDe has a Finite State machine made of three macro states:

• The Idle Macro State: the node is waiting for a General Reset coming from upper layer nodes in order to start its initial procedures whose tasks are to provide the requested information for the following regime phase.

• The Initial Macro State: the node is started but it doesn’t know the basic information for a correct implementation of the Winsoc processing. For that reason the radio approach is a pure CSMA (Carrier Sense Multiple Access);

• The Steady Condition State: the node implements correctly the Winsoc processing following a TDMA approach.

As briefly mentioned above, the nodes wait for the reception of a reset message from high level nodes to enter the Initial Macro State.

The following tasks will be accomplished in this state:

• 3etwork discovery, to obtain local information about neighborhood

• Distributed slot assignment solution, to provide a time slot to each node without the need of a central entity

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• Frame size definition, to define the dimension of the frame containing the time slots, that is to say to define the periodicity with which each node transmits (once the time slot duration has been fixed)

• Initial time synchronization, to provide a first time alignment

One of the peculiar features of the current state is the execution of the DRAND algorithm whose aim is to assign a time slot to each node in a totally distributed way. It is an efficient algorithm since it assigns the lowest possible time slot number, thus allowing the reuse of resources.

Once that all the procedures belonging to the Initial Macro State are accomplished the node enters the Steady State, where the effective data transmissions take place.

The following task will be accomplished in the current state:

• Internal state transmission, during the assigned time slots

• 3eighbors’ state reception, during the time slots assigned to the neighbors

• State update, according to the coupling algorithm

• Time synchronization maintenance

• Power reduction procedures

The use of TDMA access scheme implies the definition of a frame structure that allows each node to know when updating its internal state according to the characteristic state equation, that is the end of the frame where all the one hop neighbors contributions have been received.

Besides, the use of a scheduled medium access scheme allowed to execute some simple mechanism to reduce the power consumptions; one of these is the sleep scheduling procedure, according which each node turns off its radio when is aware that no-one of its one hop neighbors is transmitting.

An iterative mechanism is also used to maintain time synchronization among nodes, exploiting the time of arrival of the data packets, without the need to use further specific messages.

Each node transmits always in broadcast so no routing procedures have been developed, following the project’s philosophy to reduce as much as possible the use of a traditional layered structure.

Test on Fields

Tests on field for Forest Fire (in Czech Republic) and Landslide detection (in India) demonstrated, that Winsoc approach could bring new quality of forest fire protection, but that there were completely necessary to change paradigm for

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monitoring. Current methods described in literature are usually based on centric model, where decision it taken in central database and where is usually used limited number of accurate high cost sensors. The Winsoc decision is based on decentralized consensus.

Fig. 11. Landslide Deployment Diagram

The advantage of Winsoc approach has been demonstrated, if high cost accurate sensors will be possible to replace by higher number of sensors with lower accuracy of measurement. This could be guarantee due local or global consensus in WSN. The current research work demonstrated, that there is necessary to solve problem globally and then for design of nodes will be necessary taken into account three requirements:

• Requirements for algorithms

• Requirement for information extraction

• System requirements

Here will be necessary also combine different constrains coming from different areas, for example density of nodes will be influenced by three different aspects;

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maximal communication distance of two nodes given by used modulation technology, maximal range, in which different parameters is possible observed, if we need guarantee full coverage of area and requirements from algorithms to guarantee consensus in network. The density will be defined probably by lowest distance.

Fig. 12. Place of testing – Forest glade

Very specific case is direct monitoring of forest fire, where is relevant more to monitor changes in topology of network, then measure concrete physical parameters. This gives large opportunity of such solution, because cost will be given only by cost of node, not by costs of single sensors, which is usually higher.

For Land slide scenario dielectric moisture content sensors can be deployed on each and every sensor column in the landslide monitoring deployment area and the distributed consensus algorithm can be implemented for retrieving moisture content data. It may be possible to use either another network operating on a different frequency or a multiplexing scenario to collect distributed consensus values on other sensors, such as pore water pressure sensors at greater and lesser depths, or on other sensors. At the same time it should be noted that these sensors are costly and are thus not densely or uniformly installed. However, it is relatively easy to uniformly and densely deploy dielectric moisture content sensors in the landslide scenario. This will prove to be a valuable way to validate the WINSOC distributed consensus algorithms in scenarios with a smaller number of nodes.

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EarthLookCZ - GMES data publication, combination

and sharing on the web

Petr Horak¹, Sarka Horakova², Karel Charvat³, Martin Vlk4

¹WIRELESSINFO, Cholinská 19, Litovel, Czech Republic ([email protected]) 2HF Biz s.r.o., Slovanska 21, Sumperk, Czech Republic ([email protected])

3CCSS, Radlicka 28, Praha, Czech Republic ([email protected]) 4Help forest Ltd., Slovanska 21, Sumperk, Czech Republic ([email protected])

Abstract: How to work with GMES data? The EarthLookCZ project looks for solutions to connecting GMES data, how to publish your own data and combine it with others and how to create new services from available data and share them on the web … The technical output from the project, a prototype of the EarthLookCZ portal, is of course only one from the several possible answers to these questions. The project’s solution is based on the idea of implementing several independent tools for geo-spatial data searching, data management and visualization into portal and to give users the possibility of working with their own data together with data from external sources. Also an implementation of INSPIRE principles is one from the most important steps in portal development. EarthLookCZ portal presents a new way of utilizing GMES data.

Keywords: GMES; INSPIRE; Spatial data; OGC; Core services.

1 GMES

Global Monitoring for Environment and Security (GMES) is a European initiative

aimed at providing stable, reliable and timely services in the fields of environment

and security. This initiative is built on the basis of cooperation between the

European Space Agency (ESA), which ensures the implementation of various

spacecraft components and coordination centers in Europe, and the European

Commission, which creates a basic concept, defines the priorities and manages

the survey and development of services based on local data and data from remote

sensing.

The GMES together with the planned Galileo satellite navigation system are the

main pillars of the European space policy. The introduction of a comprehensive

system that will include technology for remote sensing and local data collection

and simple distribution methods, will hopefully contribute to the introduction of

highly efficient services in various areas. These services exist today, but only at

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national or regional or field level without important joint coordination. From a

pan-European point of view, the crucial thing is to ensure the possibility of using

these services repeatedly, organizing and making them available as easily as

possible. The first step has been done through the launch of the first "Core

Services". It is very important to now find the best way in which we can move

forward. For this reason, great emphasis is being placed upon the use of

geospatial information and the harmonization and efficient management of spatial

data across Europe. Also stress is being placed on the implementation of I3SPIRE

(Infrastructure for Spatial Information in Europe) as a guideline for infrastructure

and management for the use and sharing of spatial data.

2 Project EarthLookCZ - Introduction

Project EarthLookCZ (www.earthlook.cz) is one of pilot projects developed in the Czech Republic in the ERA-STAR regions framework. The project undertaken by the WIRELESSINFO association aims to verify the validity of spatial data infrastructure quality for GMES in the Czech Republic and is supported by the Ministry of Education, Youth and Sports. A non-profit association WIRELESSINFO (www.wirelessinfo.cz) is a virtual research centre, which works on information technology development mainly in the areas of forestry, agriculture, environment and e-governance sectors.

One of the main goals of the EarthLookCZ project is to support the implementation of GMES in the Czech Republic. The first project report Analysis of GMES introduces GMES tasks in scope of overall European politics in the area of space research and describes present GMES activities at both European and national levels. There is focus on GMES projects, which are currently being solved in the Czech Republic, and activities, which essentially influence solving of the EarthLookCZ project. The main focus of the activities at the moment is the implementation of I�SPIRE directive (Infrastructure for Spatial Information in Europe). One part of the study creates summaries of existing data sources of governmental sector, which might have a prospective connection to GMES activities.

From a technical point of view the project aim is the Technological infrastructure proposal based on the implementation of ISO (International Organization for Standardization) and OGC (Open Geospatial Consortium) standards for data sharing and exchange. The objective of the solving is to provide a distribution system that can ensure access to distributed data and metadata through the GMES services and also access to proper GMES data with the possibility to share and publish an organization's own GMES data.

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3 The prototype of the national GMES portal

Currently, whenever GMES data is available to users on the Internet, it is mainly as simple visualizations in the web map client. This solution makes data visualization possible, but the users have no possibility to use this data for their own purposes. A possible solution is to buy the “hard” data or use the data through standardized web services. Unfortunately only a small amount of GMES data is accessible through standardized web services now, but it seems that data sharing through web services will be the most important part of data exchange in the future.

The proposed solution of the GMES national portal in the EarthLookCZ project promotes better access to data. The prototype of the portal is aimed at sharing and publishing raster data (e.g. satellite images, orthophoto, geophysical measurements, climate data) and vector data including basic topographical layers (e.g. thematic environmental data). The main innovation of the project is the ability of users to publish their own data sources on the web and integrate their own data together with external data into new compositions. Afterwards these map compositions may be published in the form of web services (Figure 1). Users can also integrate these new compositions into their own SW solutions. This concept of the GMES portal allows not only common data visualization, but also a preparation of the new data composition by a GIS specialist and its data accessibility to other users; all of it within the portal solution.

Fig. 1. An integration of own and external sources by the new web service creations

National GMES Portal enables an integration of monitoring data that has been acquired using the space infrastructure (satellite images) and the In Situ

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infrastructure (ground measurements, aerial photographs) together with other data layers, such as general reference data (topographic maps) and thematic data (landscape planning data). Also sources of GMES Core Services built within the basic structure of the European GMES can be accessible from the portal via web services (Figure 2).

Fig. 2. Data source sharing and new services creation

Using the portal functionality, users are also able to upload their own data onto the server and publish it directly from the GMES portal. Users can combine different data sources, create new map compositions and make them available to other users. Availability “data about data” and map compositions is ensured through metadata and catalogue systems.

Overview of the basic functionality of the national GMES portal prototype:

• Data sources searching in the Metadata Catalogue – searching for external data sources or own data on the server is provided by metadata catalogue

• External geographical GMES data accessing through web services – it is possible to use external GMES data if it is accessible through standardized OGC web services. Data sources can be national or international including GMES Core services

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• Your own geo-data can be imported onto a portal and published on the web – the user is able to import his own geo-data onto the server and offer this data to others as a standardized web service. Currently, the data may be imported into file repository, but in future it is also hoped that data can be imported into database PostgreSQL/PostGIS.

• Data management of both the internal and external GMES sources – it is possible to combine external and internal data mutually and create new thematic map compositions from them

• Data visualization in web map client – all internal data, external data and new compositions are visible in a map application built into the portal

• Publishing of new composition in the form of web services – internal data and new map compositions can be published as OGC web services

• Generating of components capable of being integrated onto other web pages – the system enables the user to generate a map application HS(Open)Layers with an open API interface; the user can integrate this with other applications or web sites

• Metadata generating for the new compositions – internal data and the newly created compositions can be equipped with standardized metadata records, which will be available in metadata catalogue

The prototype of GMES portal of the project EarthLookCZ is currently being developed and modified. A present version of the portal is available at www.earthlook.cz/portal or directly from the project main web page www.earthlook.cz.

The concept of the portal is divided into 3 main parts (Figure 3):

• Sample map applications and metadata catalogue – public section of

the portal where users can work with pre-defined GMES map applications or search for GMES data sources in metadata catalogue.

• GMES data management – the most innovative part of the portal; registered users are able to import their own data onto the portal, create new map compositions, integrate external GMES sources through web services and make them available to other users as a new web service

• Sources of GMES information – links to the most important GMES web sites and public GMES web sources

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Fig. 3. Prototype of the GMES portal

The solution of GMES Data Management is based on the GeoHosting system principles. GeoHosting was developed by WIRELESSINFO members and offers services supporting the creation of a spatial data sharing system with the possibility of publishing data for any user who has access to the Web. The system is based upon open formats and is open for interaction with other SDI platforms. This model supports the re-usability of components and easy building of new applications or their modification. The goal of the design is to re-use existing tools and to define interoperable interfaces for these tools, which will therefore create the possibility of re-using these tools as a part of other applications. For the selection of the components it is important to be familiar with Open Source solutions, but only on such systems which support Open Standards (OGC and ISO)

Currently, Data Import and Map Management components are implemented into GMES portal prototype.

Data Import is an application for the management of spatial data. It supports the management of data in databases or files. It supports the export and import of this data and also publishing and updating of related metadata. In databases, it is possible to store both, vector and raster data, including their attributes. Also for

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file oriented storage, it supports both vector and raster data. From raster formats, it currently supports IFF/GeoTIFF, JPEG,GIF, PNG, BMP, ECW, from vector formats ESRI Shapefile, DGN, DWG, GML

The Map Management application is a software tool for users who want to publish or create new map projects and compositions. It supports the publication of spatial composition from locally stored data (fields or databases-stored in the Data Import application), with external WMS, WFS data services. It supports visualization in web browsers using such clients as OpenLayers, GoogleMaps, DHTML client, Desktop viewer, GoogleEarth, DIS Janitor. It can also publish data as OGC WebMapService (WMS), OGC WebFeatureService (WFS). All published data is also connected with metadata stored in Micka metadata catalogue.

Use possibilities of the portal:

The main importance of the GMES portal having the possibility of creating new map compositions from available GMES data sources and publishing of these compositions in the form of new web services. Figure 4 uses as an example of a composition compiled of data available via WMS (Web Map Services) from these organizations: CZUK – Czech Office for Surveying, Mapping and Cadastre, Cenia – Czech Environmental Information Agency and FMI (Forest Management Institute).

Fig. 4. Examples of map compositions

Czech Office for Surveying, Mapping and Cadastre provides data in the form of cadastral map, Cenia agency provides orthophotos and Forest Management Institute the forest typological map. A new developed composition can be published as a new WMS service, which can be used for example by workers doing the measurement in the field. There is obviously a possibility to connect also other web services into these compositions, Service), like WFS (Web Feature Then the final composition could be used for visualization of the actual meteorological sensors values, river level monitoring and so on.

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4 Conclusion

The prototype of the EarthLookCZ portal illustrates possible ways for GMES data utilization in accordance with INSPIRE principles. Users of the portal can search for information regarding GMES on both a national and international level. When they are registered, they are able to actively work with available external data sources, but they can also use their own data for integration with external sources, create new map compositions and make them available to other users. Publication of their own data or map compositions is joined with synchronous publication of their metadata; this functionality ensures that the new data is searchable for other users. An interaction with GMES core Services is desirable; practical examples should be available in the last period of the EarthLookCZ project.

Project EarthLookCZ does not propose to put in practice a full-value application but within the scope of a prototype to test new styles of work with spatial data in web applications. Portal functionality is of course obtainable also by other SW tools utilization, nevertheless these tools are generally expensive or high special skills are required to use them. The prototype of the project EarthLookCZ portal solutions makes these possibilities accessible for smaller organizations, schools and persons; currently these methods would be practically unavailable for them. People can test functionality of the portal after registration on the present link www.earthlook.cz/portal.

References

1. Annoni, A., INSPIRE / GMES / GEOSS, presentation. 2. COMMUNICATION FROM THE COMMISSION TO THE COUNCIL AND THE

EUROPEAN PARLIAMENT, Global Monitoring for Environment and Security (GMES): From Concept to Reality {SEC(2005)}.

3. Global Monitoring for Environment and Security, Final Report for the GMES Initial Period (2001-2003).

4. EarthLookCZ, report D12 - Specifikace GMES serveru, 2008. 5. EarthLookCZ, report D18 - Prototyp1, základní funkcionalita, 2008. 6. Harris, R., Professor - GMES AND INSPIRE - Legal and Policy Issues 7. http://www.cenia.cz. 8. http://www.czechspace.cz, http://www.czechspace.cz/cs/gmes. 9. http://www.earthlook.cz/portal. 10. http://www.gmes.info. 11. http://www.opengeospatial.org. 12. SDĚLENÍ KOMISE RADĚ A EVROPSKÉMU PARLAMENTU, Evropská vesmírná

politika, {SEK(2007) 504}, {SEK(2007) 505}, {SEK(2007) 506}. 13. SMĚRNICE EVROPSKÉHO PARLAMENTU A RADY o zřízení Infrastruktury pro

prostorové informace v Evropském společenství (INSPIRE) PE-CONS 3685/2006. 14. Šobra, J., GMES, presentation.

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Using Geohosting Principles for Publication of Users’

GMES Data within the EarthLookCZ Project

Petr Horak¹, Sarka Horakova2, Karel Charvat3, Martin Vlk4

¹WIRELESSINFO, Cholinská 19, Litovel, Czech Republic ([email protected])

2HF Biz s.r.o., Slovanska 21, Sumperk, Czech Republic ([email protected]) 3CCSS, Radlicka 28, Praha, Czech Republic ([email protected]) 4Help forest Ltd., Slovanska 21, Sumperk, Czech Republic

([email protected])

Abstract. This article continues a description of the EarthLookCZ project with special focus on the geo-spatial data sharing functionality of the GMES national portal prototype. Publication of geo-spatial data on the web, usage of GMES data stored on remote sources (external servers) and possibilities to create new web map services from such mixed data sources have been the biggest challenges of the project. Individual components for geo-spatial data management, such Dataman, MapMan or HSLayers are, have been modified and integrated together with new components into new Czech national GMES portal prototype in order to make GMES data accessible to common users.

Keywords: GMES; INSPIRE; Spatial data; OGC; Core services

1 Introduction

Management of distributed data sources is one of the principal directions in the IT development at present. As the amount of data increases, there are growing demands for systems that would facilitate their management and publication. Main requirements for these systems include the ability of fast access to up-to-date information, searching and classification of information, possibility of their use in other systems/subsystems and also their publication.

These functions are today relatively common in client applications, whether in desktop or web systems. The possibility of publication and sharing of users’ spatial data remains, however, a fundamental problem. Although there are ways of displaying users’ data in a number of web applications, tools for making users’

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geodata accessible in the form of web services are almost unavailable. Many users, however, cannot make their data accessible in the Internet environment.

EarthLookCZ Project, which was described in greater detail in the chapter “EarthLookCZ – GMES Data Publication, Combination and Sharing on the Web,” proposes among others a solution of the above-mentioned problems in relation to possibilities of better utilization of GMES data sources.

One of the main outputs of the EarthLookCZ Project is a portal prototype designed for work with GMES data. This portal is conceived in three main parts:

• Sample map applications and a metadata catalogue – the public part of the portal designed for work with predefined map projects and for searching data sets by means of a catalogue.

• GMES Data Management – the most important part of the portal as regards innovation – allows the user to import his data on the portal and to publish them in a map or as a web service, to combine his data with external ones accessible through web services, to publish new compositions and to create projects for mobile editing of data in situ.

• Information sources – a list of the most significant national and foreign GMES sources, including links to services accessible to the public.

2 GMES Data Management Structure

In terms of the possibilities of working with spatial data, the portal section GMES Data Management is the most important part of the portal prototype. This section is based on the components of the Geohosting system which were developed by members of the WIRELESSINFO Association in the framework of European projects NATURNET-REDIME and AMI4FOR, and also within their own research.

GMES Data Management (Figure 1) includes three main levels:

• Data – a module for importing data on the portal – it is provided by the DataMan component

• Maps – a module for creating and publication of map compositions – it is provided by the MapMan component

• Teredit – a module for creating projects for mobile editing of data in situ – is provided by the Teredit component

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Fig. 1. GMES Data Management module

The module of GMES Data Management is designed for making users’ GMES data accessible on the Internet, creating new map compositions by combining various data sources (users’ sources or external ones) and their publication on the web, possibly also for other work with data saved on the server (Figure 2).

Data for creating a new map composition can be integrated from the following sources:

• A WMS server with a known address

• A WFS server with a known address

• A WMS or WFS server found by an integrated catalogue service

• The File Repository of the GMES portal

• The Geodatabase of the GMES portal

• A geodatabase connected through ODBC

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Projects of new map compositions are defined by XML files and are saved in a part of the portal which is closed to the public. Processed projects can be published in several ways:

• By the map component of the portal (HS Layers)

• By a map visualization client on the web (openlayers, googlemaps, DHTML client)

• By a desktop map browser (googleearth)

• Through the OGC Web Map Service (WMS)

• Through the OGC Web Feature Service (WFS)

Fig. 2. Data flow diagram of the EarthLookCZ portal

The implemented metadata and catalogue system Micka meets the requirements of INSPIRE and the norms of ISO19XXX, and follows up on Metadata Portal operated by the Cenia Agency. All internal data sources are thoroughly interconnected with the metadata system; the portal facilitates recording of

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metadata for all imported and newly recorded data and services. Searching for data sources is also carried out by means of the metadata catalogue; the searching function is implemented directly into individual components.

3 Specifications of Components

The basic diagram (Fig. 3) shows the division of individual basic components of the proposed GMES portal and the relations among them. Individual external sources, upon which the system can draw, are shown in the upper section of the diagram. The system is able to work both with data stored directly on the internal server and with information accessible via web services. Data is saved in geodatabase by default, but the system is able to work also with data in individual files of different formats. Data repositories are represented by the File Repository and the GeoDatabase in the diagram.

Fig. 3. Diagram of basic components in the GMES portal

Individual SW system components are:

Data Exchange Management – a subsystem which provides physical access to data, import and export of data in files to the Geodatabase and back, access to data

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via web services providing original data (e.g., WFS), data editing (from a desktop or web client), access to data in mobile applications (mediated through Mobile Data Editor Interface). This is the main component which is worked out in the first stage of the EartLookCZ Project primarily for the WFS service.

Implementation of the DataMan subsystem from the Geohosting system is proposed for purposes of the portal.

Mobile Data Editor Interface – a subsystem allowing data to become accessible for mobile applications and their editing in situ. The solution is not tied to a specific platform of a map client (ArcPad, FieldCheck, TopoLCE, etc. can be used).

Data Publication Management – a subsystem which facilitates management of geographical data and their publication. It allows combining several data sources (internal database data, files and web services) to generate new map compositions, and facilitates their publication either directly in a selected map visualization client (e.g., DHTML, GoogleMap) or in the form of a new WMS web service. Implementation requires utilization and adjusting of the MapMan component.

HS Layers application based on Open Source SW OpenLayers has been used as Visualization Client. This component can be integrated also into other web applications.

Authorization Service provides the users with access to the portal and to individual functions on the basis of their authorization.

Metadata and Catalogue System facilitates searching for data sources and generating of metadata records. The system complies with INSPIRE requirements and ISO 19XXX standards, and allows cascade searching in other standardized catalogue systems. The system has been based on the current Metadata Portal which is operated by the CENIA Agency. Micka System, under development by the Help Service Remote Sensing company, is proposed as a metadata and catalogue system.

�ewly published web services for geodata has been made in accordance with the OGC norms.

Desktop editor in the diagram represents one of the ways how a user could be enabled to edit geographical data. Any SW allowing work with vector data can be used as an editor; a possibility to download and use SW Janitor, which is being developed by the GIS laboratory of the CENIA Agency as a freeware, is offered by default in the framework of the national GMES portal.

DataMan

DataMan is a web application designed to make users’ data accessible in the web environment. Data can be made accessible either in the form of a geodatabase or

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individual files can be uploaded directly on the internal server. DataMan works by default with PostGIS database, but other databases accessible through the ODBC interface can be also accessed on the basis of authorization. In the selected database, new tables can be made, their structure can be modified, or they can be deleted. It is also possible to make copies of existing tables and to modify these copies. Geographical data (points, lines, and areas) is being saved in the databases, and additional information of various data types (number, string, date and time, logic value) can be added to each table. This functionality can be used for example if the user needs an option to create his own database for geographical objects, which he could then edit directly in situ, perhaps using the Teredit application. The database table can be thus generated, edited and published by the user in MapMan.

Another function of DataMan is the possibility of uploading files with geographical data on the server. TIFF/GeoTIFF, JPEG, GIF, PNG and other raster data can be used and so can also SHP, DGN, DWG, GML and other vector data. In certain cases it is also possible to import vector data directly into the geodatabase and use them for example during a mobile collection of data. In publishing operations, metadata publication is facilitated also in the Micka system.

MapMan

MapMan, a web system for spatial data management, allows integration of data accessible through standardized web services (WMS, WFS) with spatial data saved in internal databases and files. All these data sources can be used for generating new map compositions in the web environment. Thus made map compositions can be displayed by the user in several ways – either in classic web browsers (OpenLayers, GoogleMap, DHTML client) or in desktop browsers (GoogleEarth). The possibility to publish these new compositions as a completely new WMS web service, or possibly as a WFS, constitutes, however, a significant part.

Map Project Manager is an upgrade of the UMN MapServer system, which is being developed at the University of Minnesota. MapMan exploits the functionality of MapServer especially in coordinate system transformation and in communication with various web services.

Project Editor (Fig. 4) constitutes the basic component of MapMan, it integrates the individual connectors onto data sources along with publication functionality. Project Editor is interconnected with Layers Storage and Symbol Storage, where individual layers and symbols can be saved. An important feature of the system is its interconnection to the metadata catalogue, which facilitates searching out of required data from external sources on the basis of metadata and also collection and publication of metadata on newly made map compositions.

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Fig. 4. Structure of the MapMan application

Data sources can be interconnected in several different ways. Internal data sources (i.e. data accessible on the internal server) can be saved in databases or in files. At present SHP files and PostGIS are the supported files and databases; however, connectors for other databases and file types can be also relatively easily implemented.

Data files are saved in predefined data directories accessible to MapMan. External data stored on remote servers are connected through WMS and WFS web services.

HS Layers

The Javascript library OpenLayers facilitates easy inserting of map windows into web pages and applications. It displays geographical data in vectors and rasters and also geographical data accessible through web services standardized by OGC, such as are for example WMS and WFS protocols. It is an Open Source solution which allows displaying of maps on the web independently of the server side. Open Layers offers a very wide functionality, which can be modified and extended still further.

HS Layers is an upgrade of Open Layers, which is being developed and modified by members of the WIRELESSINFO association, especially Help Service Remote Sensing s.r.o., with contribution from Help Forest s.r.o.

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HS Layers comprises of 4 basic parts:

• OpenLayers

The complete library OpenLayers, at present 2.7 version: this means that HSLayers includes and can do everything that OpenLayers does.

• Patches

It includes repairs and modifications of functionality which are included in OpenLayers (e.g., use of keyboard shortcuts when “drawing” the rectangle for zooming, visibility setup of the “zoomToMax” icon)

• Addons

It includes new components and functions, which are not present in OpenLayers and which further enhance its functionality. This part contains new user control features (e.g., for work with OGC Web Services, layer switchers in several versions, components for printing, etc.), classes for work with new types of map layers (MapServer layers with a choice of sub-layers, map layers representing graphs, etc.) and other functions. The user interface is defined by means of the ExtJS library.

o A list of Addons components

HSLayerSwitcher A layer switcher which displays a list of layers in a hierarchical tree structure

HSBoxLayerSwitcher A layer switcher which displays basic layers as buttons with the possibility of defining sub-layers (visually similar to buttons in GoogleMaps or Mapy.cz)

HSDrawControls Tools supporting drawing of graphic elements (point, line, polygon)

HSClick A tool that facilitates defining a location on a map with a description, which can be subsequently sent out in the form of URL

ChartLayer A map layer that facilitates displaying graphs by means of Google Chart API

HSMapServer A map layer that facilitates displaying MapServer data supporting a detailed visualization

HSOWSManager Components for work with OGC Web Services (WMS, WFS, WPS, etc.) which facilitate interactive access to these services and the display of their data

HSPrinter Components supporting map printing

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HSSearchParser Components supporting searching in displayed data

HSMapViewer A basic map window for displaying and basic work with a map. The ExtJS library is used to define user interface.

• Apps

It includes components which allow easy integration of “map functionality” into “non-map applications” (host applications). These components include public API by means of which map functions can be called directly from a host application. The following functions are supported:

o Displaying a map project defined on the server

o Displaying user defined objects (points, lines, areas) above basic referential map data

o A possibility to enter a location in a map with a further possibility of defining the final coordinate system

o Transformations of coordinates in between any coordinate systems

o Fulltext searching for objects

o A possibility of displaying any found object on a map

Authorization

“Authorization Tool” (Fig. 5) has been used for user administration and for their login. It comprises of two basic components:

• Authorization Service

o A web service providing functionality (individual methods) to client applications (tools). Methods for users’ login and logout, for collecting information (individual parameters and authorization) on logged in users and other supporting methods for user administration are available.

• Authorization Administration

o A web application facilitating administration of users.

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Fig. 5. Diagram of the authorization module

Authorization Service

Authorization Service serves for login and verification of individual users to the portal or during activation of individual applications (tools) which are available in the framework of the portal (Fig. 6). Authorization Service supports a unified login which means that after a successful login of a user, for example to the portal, no further login is necessary when starting individual applications (tools) available within the framework of the portal. During activation of a specific application (tool) the portal transfers a unique identifier of the current login (Session ID) which the application (tool) uses from then on in communication with Authorization Service.

Authorization Service is a standard SOAP web service, and thus its usage is very flexible and open. It can be used from applications (tools) developed on different platforms (Microsoft, Net, Java, PHP and others), operated in different operating systems (Windows, xNIX, Mac OS and others) and on different terminal devices (servers, desktop PC, PDA, smartphone and others).

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Fig. 6. Authorization Service

Authorization Service is designed in such a way as to make it possible to interconnect it with existing systems of user administration (Microsoft Active Directory, Open ID and others), which are then used for verification of users during login. The current version of Authorization Service facilitates verification of users who are defined in the internal database of Authorization Service or in an external system for user administration. Communication between Authorization Service and the external system for user administration uses a standard LDAP protocol in the current version.

Authorization Service facilitates work with several types of objects:

• A user – each user who wishes to work with an application (tool) and who uses Authorization Service must be defined in it. Each user has his defined parameters and authorization for individual applications (tools), to which he has access.

• A user group – it serves to group users into larger organizational units, which can have their parameters and authorization defined for individual applications (tools). Thus administration of a large number of users is made easier in the framework of one Authorization Service.

• An application (tool) – each application which is to be started from the portal must be defined in the framework of Authorization Service.

Definitions of the above-mentioned types of objects facilitate making linkages between users and applications, which define authorization and parameters (influencing the behaviour of applications) for individual user – application (tool) combinations.

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Authorization Administration

Authorization Administration is a web application facilitating complete administration of Authorization Service. The application facilitates displaying and browsing of existing users, user groups and applications, making new ones, modifying or perhaps deleting existing ones in a clear way. Furthermore, it facilitates defining parameters and authorization for individual users, user groups and applications.

Micka

The metadata part of the GMES portal is based on similar principles as the National Metadata Portal Ministry of Environment.

A catalogue service above the Micka metadata system has been launched within the framework of the project. The service facilitates:

• Enquiries according to specification CQL and OGC Filter

• Cascading (the service searches simultaneously in other catalogues)

• Work with profiles ISO 19115/19119 and OGCCORE (Dublin Core)

• Transactions, harvesting

• Displaying of the RSS channel for registration of changes

• Support of OGC CSW 2.0.0, 2.0.1, 2.0.2

Teredit

The Teredit system facilitates mutual communication and data transfer between a mobile device (e.g., PDA) and the central server (Fig. 7). Teredit was developed in collaboration with the European Space Agency ESA/ESRIN in Frascati within the framework of the AMI4FOR project and was tested in collaboration with the Forest Management Institute in Brandýs nad Labem.

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Fig. 7. Teredit

The system includes the server part Teredit – Broker and the client part installed on a PDA:

The server part of the system for mobile data collection

• Teredit Broker – a server part of the transaction system that facilitates saving data transferred from mobile devices on the server by means of open protocols

• Teredit Editor – a component which facilitates preparation of projects for updating of data in situ. By means of this component it is possible to prepare a project on the server using users’ data, or possibly data accessible through web services. This project is then accessible from a PDA with the help of the Teredit Mobile component.

• Data Validator – an optional control component facilitating checking of data correctness and completeness before they are saved in the target database, the component does not have to be included in the system.

The PDA part of the system for mobile data collection

• Teredit Mobile – it provides communication between the server and a mapping application, data transfer is provided in the transaction mode.

• A mapping application – one of the commonly available commercial applications, modified for the purposes of a specific project. For this project we propose using the ArcPad programme, or possibly TopolCE. Requirements for a PDA – operating system Windows Mobile.

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Data collected in situ are saved on the server in the database, and at the same time interconnection with a web application is worked out. It is therefore possible to send data collected in situ to the server (via GPRS, WiFi, etc.), and these are displayed in the web client immediately after validation (in case validation is switched off, data are displayed immediately) (Fig. 8).

Fig. 8. The principle of updating data using the Teredit system

System functionality:

• Access to structures and to updating is provided through Authorization Service.

• Data for editing is stored in the postgis geodatabase, (Open solution)

• Data from postgis or from files saved on the internal server can be used as referential data

• It is possible to arrange or not to display individual layers, to change symbols and colours (basic types)

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• It is possible to set the range of input values for individual attributes of objects

• A possibility to define control object forms for data input (it depends on the target map application)

• In the postgis database – a possibility of generating a table for a new object and of a definition of its structure

• Generating a table for a new object by copying structure of an existing object

• Generating displaying parameters in the arcpad builder or topol environments and their inclusion in a created project

• A preview of the processed project is available for each controlled object

• A possibility to provide a control project with metadata

TEREDIT system

• Teredit Editor – a server application providing a preparation for subsidies inspection

• Teredit Broker – a server component providing communication and data transfer between the server and mobile parts of Teredit

• Teredit Client – a Teredit component installed on a mobile device which provides communication and data transfer between the server and a target mapping application (typically TopoL CE, ArcPad)

Other services

• Authorization Service – an authorization service that provides authorized access to Teredit

• Visualization Client – a component facilitating a preview of a processed project in a web browser (map window, probably DHTML client)

• Metadata Catalogue – the Micka metadata catalogue facilitates both searching for data sources and registration of metadata records of new projects

Data sources

• GeoDatabase – editable data is stored in a database PostGIS

• File Storage – a storage of data files on the internal server; data files can be used as referential data (knowledge databases for EAFRD, HRDP, etc., prepared in advance)

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• External Sources – external data sources accessible through web services, primarily through WMS

4 Examples of Using Geohosting for GMES Data Management

Searching for GMES information mentioned in the previous chapters constitutes an important part of the proposed portal. The main importance and innovative contribution rests, however, in the possibilities offered by the EarthLookCZ portal as regards GMES data management. Users can place their own GMES data on the portal and make them accessible to other users in the form of a web service. Users can combine their data and external data sources and create new map compositions from them; these compositions can again be made accessible to other users – either by displaying in a map client of the portal or in the form of a new web service. Another way how to use GMES data on the EarthLookCZ portal is definition of a whole map component including GMES contents and its placement in users’ applications. And finally the last possibility is to use the functionality of the portal for editing and possible recording of new data by means of a thick client.

The majority of current map portals provide users with a possibility of viewing data stored on them, some of them also viewing data from remote sources which are accessible through web services, and only very few of them allow users to upload their own data and view them. Functionality that would enable users to upload their data and would make it possible for others to use them cannot be found on public webs, or only minimally. Not only will the proposed solution make it possible for users to use external data and combine them with their own, but they will be also able to make their data and data compositions from various data sources accessible to others.

The method of making users’ data public and working with them is divided into four parts:

• Publication of users’ data in the Internet environment

o Files Importation of data into a database

• Assembling a new map composition by combining external and users’ sources

o A browser built-in the portal o A new web service standardized by OGC

• Generation of a new map component to be incorporated in other systems

• Utilization of newly created services for editing data in thick clients

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o A PDA platform o A PC platform

Active work with data is made possible in a part of the EarthLookCZ portal which has registered access.

Publication of Users’ Data

Functionality of the module for publication of users’ data allows users to upload their data on the server, to provide them with a metadata record and make them accessible in the form of a web service standardized in accordance with OGC. Data can be saved in files in the data repository or in the case of vector data they can be imported in the geodatabase. The PostgreSQL database with the PostGIS upgrade is proposed as the basic geodatabase for vector data.

A Model Case of Users’ Data Publication – Use-case 1

The user has at his disposal a data set of monitoring points which are in the SHP format. He has also at his disposal his own referential raster data. The user wishes to display the SHP monitoring points in the web environment so that they could be displayed together with the referential data. He also wants these data to be not only displayed in a map browser but to be accessible from other browsers via a web service. The user fails to have the technical means to make geographical data public on his own.

Objective: Making user’s data accessible in the web environment so that they can be accessed through a web service

Used data layers:

• An SHP file of monitoring points

• Raster data in the Tiff format

Approach:

• The user enters the data management section on the portal.

• The user logs in. In case he has not registered yet, he must do so first.

• The user selects “Upload a file” in the “DataMan” module.

• The user selects a file for uploading and uploads it on the server.

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• The user opens the “MapMan” module.

• The user starts a new project for monitoring points, and selects a system of coordinates and parameters.

• The user inserts a required layer accessible in the “Internal data on the server” section into the new project.

• The user provides the project with metadata.

• The user publishes the project as a new web service – and receives the web service address.

• The user starts a new project for referential raster data and repeats the process of publication in a similar way.

Diagram:

Output: The outputs are two independent WMS map services (in case of vector it can be WFS) which have their own metadata and may be searched for by the catalogue service in the public part of the EarthLookCZ portal.

Generating a �ew Map Composition

Although at present there are not many data sources which are accessible through web services, their number is constantly rising, and we may presume that in future remote access to data will be one of the main ways of their displaying. Different data sets are required for different purposes, and these sets can become confusing due to the increasing amount of data. If a user, for example a large organization, needs to prepare a certain data set composed of general and specialized GMES data in the framework of the EarthLookCZ portal, in a standard way each of its employees would have to add specialized layers again during their work on the portal. The proposed functionality of the portal facilitates creating these new map

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compositions, saving them, providing them with metadata and making them accessible to other users as a whole – either in the form of a project displayed in a map window or as a new web service, which other users can connect into their SW.

In order to create these new compositions, users can use their own data saved on the EarthLookCZ portal, data from external sources accessible through standardized OGC services or a combination of these two sources of data.

A Model Case of Generating a Map Composition – Use-case 2

The user has at his disposal a data set of monitoring points which are uploaded on the EartLookCZ portal (the first four steps are the same as in Use-case 1). The user intends to create a new map composition that will include his own data and referential data. The user wants to combine these data sets with the data of the Cenia orthophotomap and with the data of the ZABAGED topographic map. Furthermore, he wants to incorporate in the project data on the health status of a forest, which are provided by the Forest Management Institute. All external data are accessible remotely through WMS. He wants to display the resulting map composition as a project in the map application of the EarthLookCZ portal. The user also wants to make available a part of the map project, which would include a composition of the data on the health status of the forest and of individual monitoring points, in the form of a new WMS service.

Objective: Generation of new compositions by combining data from different sources, their displaying in a map client of the portal and making them accessible in the form of a WMS web service.

Used data layers:

• User’s

o Monitoring points in SHP • External (WMS)

o Orthophoto (Cenia) o ZABAGED (Office for Surveying) o Forest Health Status (Forest Management Institute)

Approach:

• The user enters the data management section on the portal and logs in.

• The user starts MapMan module.

• The user creates a new project.

• The user selects a coordinate system and other parameters of the project.

• The user adds individual data layers into the project gradually:

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o His data from the “Internal data on the server” section o External data separately from the “WMS server” section if he

knows the addresses of WMS servers, or uses the “catalogue client” section to find them.

• The user sets the order and parameters of displaying individual layers.

• The user fills in the project metadata.

• The user publishes the project.

A Diagram of the Module for Generating a 2ew Map Composition

Output: The output is a new map composition containing the required data sets; this composition is searchable and can be displayed in the public part of the EarthLookCZ portal. The second output is a WMS web service, which makes the new composition accessible for use in other map clients.

Generating a Map Component for Incorporation in Other Systems

In case the user intends to use newly created map compositions in his own web applications, he can use the function of generating a whole map component including a composition and insert it in his application.

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A Model Case of Generating a Map Component – Use-case 3

The user wants to incorporate a map project made in the framework of Use-case 2, including a map client, in his web pages.

Objective: Incorporation of a map component, including a newly created map composition, in user’s web pages. Approach:

• The user creates a new map composition using the approach described in Use-case 2 or chooses one of the prepared map compositions.

• The user chooses publication in the form of a map component.

• The user receives a script containing a programme code of the map client and the chosen map composition.

• The user implements the code into his web pages.

A Diagram of the Module for Generating a Map Composition

Output: The output is a programme code of the map application and the web composition, this code can be placed in the user’s web pages or in the user’s system.

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5 Conclusion

Use of data sources by means of web services will become more and more significant. The solution of using web services as a basis for creating a new web service represents a way to effectively and purposefully employ data sources in making new values. As a web tool for management of spatial data of various forms and sources Map Project Manager represents a significant innovative solution, which ensures easy accessibility of external data sources, a possibility to create new services, and owing to its ability of working together with other SW components it ensures also an easy integration into complex solutions, as is the case for example with Geohosting. The technological concept of Geohosting and its incorporation into the EarthLookCZ portal facilitate publication of users’ geographical GMES data, their combination with remote data sources and possible updating in situ not only for large companies and institutions, but basically for every user working with spatial data. The solution is based on the INSPIRE principles and provides publication of users’ data including a standardized metadata record, searching for external data sources through the metadata catalogue, reduction of data replication through utilization of web services, and creation of new sources accessible in the form of web services.

References

1. New Education and Decision Support Model for Active Behaviour in Sustainable Development Based on Innovative Web Services and Qualitative Reasoning, D3.4.4, Release 4 of NaturNet-Redime portal – final release 30/10/2007,Praha.

2. AMI4FOR project, D3.1DESIGN OF FORESTRY KNOWLEDGE ANDPRECISION FARMING MANAGEMENT SYSTEM

3. Karel Charvat at all Uniform Resource Management, at Naturnet Redime Newsletter vol 6,December 2007, ISSN 1801-6480

4. G. A. Papadopulos, G. Wojtkowski, W. Wojtkowski, S. Wrrycza, J. Zupancic: Information Systems Development, Towards a Service Provision Society, Petr Horak, Karel Charvat, Martin Vlk: Web tools for Geospatial Data Management, ISBN 978-0-387-84809-9, Springer 2009

5. NaturNet-Redime project websites: http://www.naturnet.org, http://portal.naturnet.org 6. Ami4for project web site: www.ami4for.org 7. EarthLookCZ project websites: www.earthlook.cz

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Geoportal for everyone

Premysl Vohnout1, Jachym Cepicky2, Stepan Kafka2

1Czech Centre for Science and Society,

Radlicka 28 150 00, Praha 5, Czech republic

[email protected]

2Help Service – Remote Sensing s.r.o, 256 01, Benesov, Czech Republic

[email protected]. [email protected]

Abstract. This paper will describe capabilities of HSRS1 Geoportal. Our product is used in several European projects (e.g. Plan4all, Metaschool, EarthLook, Envirogrid), and it is developed by association of Czech Centre of Science and Society, HSRS and Help Forest. Geoportal is package of applications; it is a set of independent components which can be arbitrarily interconnected. Geoportal can be compiled from all of these applications or none of them (except map component).

Keywords: Geoportal, INSPIRE, standards, spatial data, web services

1 Introduction

Geoportal is a site which allows users to search, view, examine and share spatial and non-spatial data. Geoportal is based on interoperability standards (OGC, W3C, OASIS, ISO) which are connected to other web-based resources and helps to create a distributed structure of information and knowledge based on spatial localization. Geoportal should not be closed central storage of spatial data without possibility of redistribution of this data. Geoportal should be solution, which does support the searching of data and information and their viewing and using by external sources.

1.1 Geoportal structure

Geoportal is a package of stand-alone applications. Every geoportal can have different set of these applications. The main purpose of this product is to be

1 HSRS – Help Service Remote Sensing

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“INSPIRE compliant”. However, only one part of it – metadata – can be INSPIRE compliant right now; other parts of INSPIRE are still under discussion and development. The INSPIRE Directive requires the EU member states to establish common infrastructure pro publication of public service geodata. Member states are obliged to open the access to metadata through the INSPIRE Discovery services and data through INSPIRE View and Download services. These services can be made accessible through geoportals such as INSPIRE, a common European geoportal, or via other narrowly focused portals which also include national portals.

Architecture is based on Service Oriented Architecture which allows integration with other resources and other portals. Main idea is to use as many as possible open source products and standards. Main purpose of this portal is to take care of spatial data but it allows using Open Search technology and publishing non-spatial data as well.

1.2 4th way

Portals and spatial data can be divided onto 3 groups.

1. Public administration - this group is oriented on INSPIRE. Data stored on these portals have their life cycle. This means that these data are acquired every day, week, month, year, etc., and it is known when these data were gathered.

2. Public portals – Google, Yahoo and some others can be assigned to this group. These are used by millions of ordinary users who are looking for certain information on daily basis. Most of such data can not be used as we don't know e.g. their property rights, licensing, or time of creation of data.

3. Online communities – best known system in this group is probably the OpenStreetMap. This is an open source spatial data system which is available all over the world. Data are created by everyone who knows how to do it. Problem is that these data are continuously modified and do not have conditions of regular updating. Big advantage of it is its tremendous human power.

4. The 4th way – data from all groups can not be utilized simultaneously right now. However, what if some possibility is discovered that would enable to put “INSPIRE data”, GeoRSS, KML, RDF, OpenStreetMap, etc. into one portal?

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2 Applications

2.1 MIcKA

The MicKA Metadata Catalogue is used as site where metadata can be put to metadata storage and published as a catalogue service by CSW (Catalogue Service for Web). MIcKA is used by several institutions and projects, e.g. by Czech Ministry of Environment, Czech Geological Survey; among Projects the Plan4all, Metaschool or Naturnet can be named.

This product is translated to 16 languages as it is used in several Europe-wide projects. It comprises GEMET and INSPIRE integrated thesaurus as well. It allows import of several formats (ESRI ArcCatalog, MIDAS, WMS, WFS, CSW). It supports the OGC CSW 2.0.2 (+ISO AP 1.0) catalogue service. Important for European projects is the support for INSPIRE profile. Metadata can be put-in or retrieved by CSW-T.

Fig. 1. Metadata Catalogue MIcKA

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What was added lately is a support for OpenSearch. This search can be put directly into web browser to the upper right corner search field (Google or Bing search engines are always available here) so the search can be made directly in browser without any need of going to the page with search field.

2.2 Catalogue Client

Catalogue Client allows searching through connected metadata catalogues by catalogue service OGC CSW. Data can be searched by text or by elements defined in standards (OGC CSW 2.0.2, AP ISO, INSPIRE). Basic elements are sets of data and services. Basic elements can be extended for other sets by user demands but they will not be searchable on other catalogues. First version of catalogue used cascading of multiple services. Current version enables adding other services independently on each other.

Fig. 2. Catalogue client

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This application interacts with a map viewer so the map services can be added into a map by one click. Another interaction is performed with metadata extractor. Documents or web pages stored by extractor can be opened by one click as well.

Services can be added from a list of pre-defined services or by direct link.

2.3 Map Viewer

The HSLayers system is used as a Map Viewer. This application has been developed by HSRS Company. Core of HSLayers system is the OpenLayers, a JavaScript web map client. Big difference from OpenLayers is in the appearance, as the OpenLayers has much more functions but very simple design. The Ext JS – JavaScript framework – is used here for design in HSLayers. This allows more complex designing.

The source of HSLayers consists of two main parts, patches and add-ons. Patches are small modifications of OpenLayers original code. As OpenLayers developer style has big demands on developers, it is always very difficult to get these

Fig. 3. Map Viewer

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patches to source code; these patches must be hold outside the source code. Add-ons are new functions which are written by using “pure” OpenLayers or ExtJS. Big emphasis has been put here on its translations lately; versions in Latvian and Spanish have been made available recently.

One of the new functions which is very well visible on the screen is a side panel enabling for example map prints, adding new service by OWS2 Manager, etc. Projection switcher is available as well. If the service which is added by OWS Manager is in projection that is not supported by a map application, using the transformation service which is also part of INSPIRE draft is possible.

2.4 Metadata Extractor

Main purpose of geoportal is to administer the spatial data, but a need of publishing of non-spatial data (documents, web pages …) can come as well. This is performed by Metadata Extractor, a web application using very simple form. Thanks to this, it is very easy to use. It is only needed to specify which file or URL is desired for publishing; user has to fill in the remaining fields and then only click to save the metadata. This application also allows filling-up some fields

2 OWS – Open web services – WMS and WFS

Fig. 4. Metadata Extractor

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automatically from metadata inserted into documents (for example Microsoft Word document). Metadata are stored in MIcKA in Dublin Core Standard which is specialized for non-spatial data. Metadata Extractor also allows publishing the whole pages. The only thing needed is to put all contents into one zip archive.

3 The present and the future

The INSPIRE is still from bigger part in a draft stage [1][2]. Only the part which is now stabilized is metadata [3] so this determines the direction of development. Core of MIcKA can be called a stable version. On the other side, the Map Viewer and transformation services are still in intense development.

Some new functions will be added to geoportal in a near future, for example some CMS for easy publishing of news. This will also include some RSS feed so it will be possible to fetch the news in his or her favorite news reader. There is also a plan to add more sophisticated extraction of metadata into Metadata Extractor.

Architecture of geoportal allows constructing the instance which will fit to project demands. There is also possibility to integrate other applications which were not developed for the use with geoportal.

4 References

1. INSPIRE Network Services Drafting Team: Draft Technical Guidance: Discovery Services (2009) [online]. URL:

2. <http://inspire.jrc.ec.europa.eu/reports/ImplementingRules/network/D3.7_Draft_Technical_Guidance_document_Discovery_Services_v1.0.pdf>

3. Data Specifications Drafting Team and Annex I Thematic Working Groups: Draft Technical Guidance: View Services (2009) [online]. URL:

4. <http://inspire.jrc.ec.europa.eu/reports/ImplementingRules/metadata/MD_IR_and_ISO_20090218.pdf>

5. European Commission Joint Research Centre: INSPIRE Metadata Implementing Rules (2009) [online]. URL:

6. <http://inspire.jrc.ec.europa.eu/reports/ImplementingRules/metadata/MD_IR_and_ISO_20090218.pdf>

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Sensors and Analysis in Web Environment

Karel Charvat1, Jan Jezek2, Jachym Cepicky2

1 Wirelessinfo, Cholinska 1048/19, 784 01 Litovel, Czech Republic, [email protected]

2 University of West Bohemia in Pilsen, Univerzitni 8, 306 14 Pilsen, Czech Republic, [email protected]

3Help Service – Remote Sensing s.r.o, 256 01, Benesov, Czech Republic, [email protected].

Abstract. The aim of the paper is to describe the implementation of Open Geospatial Consortia standards for integration of sensors into Spatial Data Infrastructure and for Data Analysis in Web Environment. Both are important contributions to implementation of INSPIRE and GMES in the Czech Republic. These standards implemented as Open Source are also used in other projects like Winsoc or EnviroGrid Black See.

Keywords: OGC, SWE, SOS, WPS

1 Introduction

Implementation of INSPIRE, GMES and GEOSS requires not only access and discovery to existing spatial data infrastructure or to repositories of Earth observation data, but there is also need for support for in situ monitoring and also for online data analysis.

The advanced hardware-based solution is described in [1], this paper is focused on software integration of sensors measurement with SDI. The paper describes a solution which was designed in cooperation among WirelessInfo, Czech Centre for Science and Society and West Bohemia University and which is now integrated as a part of Earthlok architecture.

For the purpose of spatial data analysis Open Source library PyWPS was designed and developed which is currently released in version 3.0.

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2 Sensor Web

The concept of sensor web was introduced by NASA. The sensor web enables autonomous collaborative observation collections via a variety of sources. Typically, scientific events of interest trigger observation campaigns in an ad hoc sensor constellation and supply multiple data acquisitions as rapidly and to such extent as possible in a given time period. This is accomplished through a seamless set of software and communication interactions in a system of linked sensors. [2]

As the critical management is becoming more up to date, regarding communication with GIS tools, the OGC begins to release the Sensor Web Enablement (SWE) that should become a standard in integrating various kinds of sensors into one communication language and well defined web environment. Open geospatial consortium SWE is intended to be a revolutionary approach for exploiting Web-connected sensors such as flood gauges, air pollution monitors, satellite-borne Earth imaging devices, etc. The goal of SWE is the creation of web-based sensor networks. That is, to make all sensors and repositories of sensor data discoverable, accessible and where applicable, controllable via the Internet. Open geospatial consortium defines a set of specifications and services for this goal. Short descriptions of these services are shown below. [3], [4]

Sensor Observation Service

The SOS is an OGC standard that defines a web service interface for discovery and retrieval of real time or archived data. Data are produced by many sensors, including mobile, stationary, in-situ or remote sensors. Data can be observations or descriptions of the sensor (calibration information, positions, etc.). Observations return encoded as an O&M Observation and the information about the sensor returns encoded in SensorML or TML.

The operations of the SOS are separated in four profiles:

• core profile – three basic operations, provided by every SOS implementation

• transactional profile – operations to register sensors and insert observations into SOS

• enhanced profile – additional optional operations

• entire profile – implements all operations

Core profile has three mandatory core operations which provide its basic functionality:

• GetCapabilities – returns a service description containing information about the service interface and the available sensor data.

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• DescribeSensor – returns a description of one specific sensor, sensor system or data producing procedure. The response returns information like position of sensor, calibration, in- and outputs encoded in SensorML or in TML.

• GetObservation – provides access to sensor observations and measurement-data.

Our recent work was focused on creating an SOS implementation which contains core operations. Communication between consumer and implementation is based on xml documents.

An XML schema describes the structure of an XML document. An XML Schema:

• Defines elements that can appear in a document;

• Defines attributes that can appear in a document;

• Defines which elements are child elements;

• Defines the order of child elements;

• Defines the number of child elements;

• Defines whether an element is empty or can include text;

• Defines data types for elements and attributes;

• Defines default and fixed values for elements and attributes.

For reading and parsing XML document, JAXB utilities that are a core part of JAVA are used. JAXB constitutes a framework for processing XML documents.

JAXB accesses the XML document from a Java program by presenting the XML document to the program in Java format. The first step in this process is to bind the schema for the XML document. Binding a schema means generating a set of Java classes that represents the schema. All JAXB implementations provide a tool called binding compiler to bind a schema.

We have successfully generated all required classes, so now we can handle all SOS related XML documents. Next work is to add a convenient API to deal with specific requirements of SOS more comfortably.

This lets us publish the position or the track of the sensor and some of the measurements. To publish the measurements in a better way, we can access the data by SOS service (still in development). We have also implemented web service that generates charts from database query.

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Fig. 1. Client based on Google Earth

One of the numerous possibilities is to access the data by Google Earth. Other possibility is HSlayers based client. The sensor track can be visualized as mash up with Google maps in OpenLayers application. New web application was implemented for measurements charting.

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Fig. 2. HTML based client

Fig. 3. HSlayers client

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The sensor position can be visualized by any WFS client. Observed values are available in the form of chart (PNG image) and they are available by web service (http GET) where one of the parameters is ID of the feature representing sensor position.

There are many possibilities of dealing with sensor measurements using free and open source software. The described approach can easily be used for tasks like car monitoring or others by using almost free technologies.

Nevertheless, the complex and interoperable solution that can deal with all sensor based tasks (e.g. alerts, sensor processing) is still an open issue. Even the OGC initiative was putting a lot of effort into this task recently. The reason is that the implementation support for this specification is still rare. It would be really amazing if GIS and sensor community could reach the conformity and bring the topic of sensors and measurements to the same level of interoperability as for example spatial data sharing by WMS, WFS and WCS standards.

3 WPS

The OpenGIS® Web Processing Service (WPS) Interface Standard provides rules for standardizing inputs and outputs for geospatial processing services [5]. The standard describes the way of distributing geospatial operations (referred as “processes”) across networks. WPS server can be configured to offer any sort of GIS functionality to clients across network. The process can be simple calculation, like putting raster maps together or making buffer around vector feature, as well as complicated models, as for example climate change model. [6]. The main goal of WPS is that computational high-demanded operations are moved from client stations (general desktop PC) to server.

Three types of request-response pairs are defined. Request can be in Key-Value-Pairs (KVP) encoding, as well as XML document. Server response is always formatted as XML document.

• GetCapabilities - Server returns Capabilities document. First part of the document includes metadata about server provider and other server features. Second part of the document includes a list of processes available on server.

• DescribeProcess - Server returns ProcessDescription document. Apart from process identifier, title and abstract, process in- and outputs are defined.

• Execute - Client overhands necessary inputs for partial process, the server provides geospatial calculations and returns document with all process outputs.

Three basic types of in- and output data are defined:

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• LiteralData -- Character strings as well as integer or double numbers.

• BoundingBoxData -- Two pairs of coordinates

• ComplexValue and ComplexValueReference -- Input and output vector and/or raster data. Vector data (e.g. GML files) can be directly part of request/response execute document (then the input is of type ComplexValue). Client can specify only URL to input data (e.g. address to Web Coveradge Server (WCS)). In this case, the data are of type ComplexValueReference.

4 PyWPS

PyWPS is a project which has been developed since 2006 and which tries to implement OGC WPS standard in its 1.0.0 version. It is written in Python programming language. The main goal of PyWPS is that, from the beginning, it has been written with direct support for GRASS GIS. Consequently, PyWPS can be conceived, as a kind of translation library which translates requests complain to WPS standard, overhands them to GRASS GIS or other command line tool (such as GDAL/OGR, PROJ.4 or R statistical package), monitors the calculation progress and informs the user and after the calculation is completed, it returns its result. PyWPS released under terms of GNU/GPL licence. Currently, version 3.1.0 is available.

Fig. 4. PyWPS implementation

References

1. Paolo Capodieci, Fabio Mengoni, A novel approach to Environmental Monitoring System for Landslides and Fire detection (in this publication

2. http://eo1.gsfc.nasa.gov/new/extended/sensorWeb/sensorWeb.html 3. Karel Charvat, Ota Cerba, Josef Fryml, Martin Pospisil, Petr Horak, Jan Jezek, Petr

Kubicek, Marek Musil, Zbynek Krivanek, Avi Gal, Paolo Capodieci, Maris Alberts

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Forestry in situ monitoring and data management, IAALD AFITA WCCA, 2008, Tokyo

4. Charvat K., Jezek J., Musil M., Krivanek Z.: EnviroGRIDS interoperability guideline EnviroGRIDS Deliverable 2.3, p.25. (2009)

5. http://www.opengeospatial.org/standards/wps#overview, 6. Jachym Cepicky PyWPS 2.0.0: The presence and the future,

http://geoinformatics.fsv.cvut.cz/gwiki/PyWPS_2.0.0:_The_presence_and_the_future 7. http://pywps.wald.intevation.org/

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Monitoring of air pollution damage to forest

Vladimir Henzlik1, Josef Fryml2

1,2 Forest Management Institute, Nabrezni 1326, 250 01 Brandys nad Labem, Czech

Republic [email protected], [email protected]

Abstract. Theory of the Air Pollution Threat Zones in forest was backed up by the Forest Management and Game Research Institute, Jiloviste-Strnady, in about 1958. They serve as a practical tool for forest management differentiation within the forest facing pollution load, the very negative anthropogenic factor causing health decline in large areas of Czech forest.

A three-step system of damage classification has been chosen and it is in use up to now. The scale of damage to one individual tree was defined as the percentage of needle loss, defoliation. Damage status of forest stands, the Stand Damage Degree, was classified by the means of the share of strongly damaged trees from the total trees inside the stand. Classification of damage dynamics is the third step of system. According to rapidity of the stand damage degree change, Air Pollution Threat Zones have been delimited within all the Czech forest. These were derived from sampling of damage in the Norway spruce stands.

Subjective human interference into classifications executed by various assessors in the field was eliminated using the LANDSAT TM-5 satellite imagery. Damage and mortality classification was processed by STOKLASA Tech. Prague. Time series of such classified scenes and about 1100 temporary sample plots based the 1995 Zones objectification within all the Czech forest. Using the Czech scale, damage and mortality showing maps by STOKLASA for periods of 1984-85, 1986-88, 1990-1992, 1993-94, 1994-2007 are accessible at present. Similar maps showing average stand defoliation by 10% steps are also in disposition.

The Forest Management Institute (UHUL), Brandys nad Labem, provides a web application based on Mapserver since 2005, with the support for web services. Unique information from those LANDSAT TM images (time series 1984-2007) has been opened up there as seamless map composition for entire area of the Czech Republic.

The Czech Ministry of Agriculture has to provide and to establish geo-informed products and services to support GMES, utilize available Earth Observation resources, and integrate them with existing models into preoperational end-user applications. These web applications “Forest damage” and “health condition “, and the “Regional Plans of Forest development ” solution will help to fulfill the strategic goals of GMES by supporting the data source harmonization in the field of

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natural resource monitoring, providing data systems for timely warnings as well as by the adoption to information needs of the regional users. The output will contribute to the identification of possible threads, fast response and provision of relevant analytic data within the GMES for forestry sector with objective on sustainable forest management.

URL: http://geoportal2.uhul.cz/mapserv/php/mapserv3.php?project=landsat&

Keywords: Forest health status, web service , air pollution threat zones in forest, WWW, Internet, data sharing, network, information, server, damage zones of forest, the land cover monitoring, forest damage monitoring, Support of Global Monitoring for Environment and Security (GMES)

1 Introduction

Subsidies for the management of forest under air pollution load are differentiated according to the so called Air Pollution Threat Zones as well as the practical management method models are.

At present, the Zones are backed up by the Decree of the Ministry of Agriculture no. 78 1996 Coll. A Zone is defined as „the forest region with similar dynamics of the forest stand damage decline, expressed by the forest stand damage degree increment in one decade.

Health status and decline dynamics are now derived from the Landsat satellite imagery and serves as the basic information on forest damage, mainly the damage caused by air pollution. In the satellite imagery data, information can be found enabling the vegetation status characterization.

Among them it is the information on health status of the forest stands affected by air pollution, biological damaging agents, site condition, and human interference into forest. Assessing defoliation change dynamics, it is possible to delimit zones of threat and decline risk decisive for future forest management and protection.

The delimitation of the Air Pollution Threat Zones to forest on the base of satellite imagery had following aims:

• Continue in the forest health status monitoring as a base for delimitation

of Air Pollution Damage Zones to forest monitoring in terms of the Forestry law (no. 289, 1995 Coll., and of the Ministry of Agriculture Decree no. 78, 1996 Coll.

• Prepare an objective base for forest recuperation activities (liming, chemical amelioration) and also for a proposal of the stabilizing and site improvement tree species ratio in reforestation.

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• Prepare an objective base for tax breaks and benefits, and state subsidy politics.

Solution came from formulation and defining of forest manager practical needs. In the decision process the forest manager requires to know not only the health status of single tree and a of forest stand, but also to have a possibility to assess the future development of them. The classification must be as simple as possible in the same time being easily visually assessed on base of one or small number of characteristics. This request in principle brought some simplification and distortion. However, mistakes and errors caused by misunderstanding, short experience, and subjective opinions of numerous practical forester has been reduced strong

For those reasons, defoliation of crown was used for one tree damage classification, share of the heavily damaged (defoliation more than 50 %) trees was applied into stand damage degree classification, and rapidity of the Norway spruce forest stand damage degree increment if employed for the Air Pollution Threat Zones delimitation.

In the Zones, model sets of recommended management methods have been modified and differentiated (Plíva, 1991) according to the stand damage degrees and pollution threat (Materna, 1958, 1973; Henžlík, 1989, 1990). Owners managing forests in the Zones of highest treat receive tax breaks and benefits, and management higher costs compensative.

In comparison with methods used in neighboring countries, described system is better: more complex and enabling solution of related problems. Ecosystem access preceded the time and it is still unappreciated.

1.1 Defoliation

Defoliation - needle loss; a reduction of live foliage volume in comparison with a

locally usual amount of assimilation organs, which was not caused by biotic

damage agents (insects, fungi, lichens, parasitic herbage) nor climatic factors

(frost, icing, wind) usually was interpreted as an effect of anthropogeneous

affects, mainly of the air pollution. For this purpose, defoliation was considered the main and decisive symptom of the air pollution caused damage. The defoliation has been and it is up to now the determinant characteristic for the single tree damage degree (and being applied for the stand damage degree) definition.

Higher presence of sulfur and fluorine in foliage was considered a proof of air pollution affect. Fluorine was taken as the proof of pollution origin from the so called Black Triangle (borders of East Germany, Czechoslovakia, and Poland).

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1.2 Single tree damage degree

Damage degree of one (individual) tree has been defined by the percentage of

loosed needles or leaves in comparison with a locally common amount of

assimilation organs on the similar tree class (level position in the stand).

Wolfs, reserve, and substitute shoots has been also considered, because this foliage is a symptom of regeneration capability. On the contrary, defoliation caused by the agents other than pollution was excluded from the indication. Pollution affect was characterized by loses of the oldest needles in a crown. The other damage started from the youngest needles.

Concerning broadleaves (oaks, beech, and Birch), the main characteristics of pollution damage are changes in growth of branches (reduction of secondary and tertiary small branches), foliage in clusters (usually on the tops of branches), terminal small branches dying, and finally dying of the main branches in the crown (Westman, 1990; Metodický návod 1988). Another symptom is: early yellowing or discoloration, dieback, and fall of leaves, all observable already in August or early September.

Single trees are denoted using Arabian ciphers starting with 0 and with 5 ending the higher number the higher damage is.

Similar damage classification based on the defoliation percentage, expressed directly in % or by the means of some classification key, has been used in statistical monitoring activities, domestic and foreign (ICP – Forest) and in research. In the damage beginning, these can serve as an indicator of trees to be extinct during thinning.

Air pollution damage to forest monitoring has a long tradition, in the Czech Republic. On permanent sample plots in neighborhoods of the Trutnov power plant, North Bohemia, Prof. Tesař has monitored pollution affects and forest recuperation for more than 50 years there. Damage change on individual trees was monitored in research plots by the Forest Management and Game Research Institute (FMGRI), Jiloviste-Strnady (Kučera, 1979; Tichý, 1988) and in the same time in permanent sample plots by the FMI (Pospíšil, 1979). Initially, permanent sample plots were an individual activity of FMI specialists starting by branch offices located in the most polluted areas since 1950´s. Since 1980, uniform series of permanent sample plots have been established to monitor the damage (defoliation, mortality, and increments).

Damage degree of an individual Norway spruce tree is defined by defoliation percentage in the Ministry of Agriculture Decree no. 78, 1996 Coll. The definition has not been changed since the 1960´s. In the previous legislature (Metodický návod, 1988), definition valid for pine was included similar to the one for Norway spruce. Initially, before 1981, the both scales highly differed one from the other. Concerning oaks, beech, and birch, Slovak and Swedish experiences were implemented.

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Damage degree of single tree can vary in response to the changes of pollution load and weather in the course of previous and present years. After years of pollution affect, rapid and lasting regeneration is less probable.

Table 1. Single tree damage degree

(�orway spruce)

Damage degree Crown defoliation, %

symbol characteristic

0 healthy tree 0

1 slightly damaged tree 1 - 25

2 medium damaged tree 26 - 50

3 heavily damaged tree 51 - 75

4 dying tree 76 - 100

5 Dead tree 100

Decree No. 78/1996 Coll., Ministry of Agriculture

The Czech scale of single tree damage classification is similar to scales used in international monitoring programs (ICP - Forests, 1992).

Main classification problem inheres in the needs to compare real tree crown with a fiction, an image of healthy and „fully foliated tree” within the region and forest site. Subjective assessments lead by numerous assessors differed between regions and calibration workshops domestic or international assessors did not reachdesirable objectivity improvement. Because of this, ICP – Forest program in some time resigned in comparing the damage statuses between individual countries. Local differences of damage classification did not reduce monitoring results applicability in the practical forest manager decision process. Use for comparing damage of various Czech regions has been also possible.

1.2 Forest stands damage degree

Management of particular forest land (forest ecosystem) lot is determined by the status (and by the predicted development of that status) of all the trees inside it.

Forest stand damage degree is given by percent share of trees showing

determined degree of damage from all the trees inside a management unit

(compartment).

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Forest stand damage degree was denoted using Roman cipher (higher number means higher damage). Originally, there were only four numbers (I to IV) i.e. damage degrees in the system. Later, an „initial damage degree“ (0/I) has been added and the III degree has been divided into two halves, a and b. Up to now, the main characteristic of a forest stand damage degree continues to be the percentage of heavily damaged, dying, and dead trees from the total trees inside a forest stand. It means in spruce, fir, and pine stands the trees with defoliation higher than 50 %. In the case of broadleaved trees (oaks, beeches and others), crown skeletal branches are dying on heavily damaged individuals.

The scale has an irregular size of characteristic for individual degrees purposely: increment of damage degree in time for to be approximately linear.

Forest stand damage degree can oscillate, too, especially at the beginning of the pollution influence. Starting with the IIIb degree, the damage is usually irreversible. .

Enlistment of a forest stand into the stand damage degree was one of deciding characteristic for future management activities (suitability and safety of thinning, beginning and form of regeneration, and choice of species in reforestation). Slight subjectivity of damage degree assessment has not an important influence onto data usability.

Table 2. Forest stand damage Degree

(�orway spruce mature stand)

Stand damage degree Single tree damage degree

0 1 2 + 3 + symbol characteristics maximum share from all trees, %

0 healthy stand 100 0 0 0 0/I first symptoms of damage 99 20 0 0 I slightly damaged stand 32 5 II medium damaged stand 84 30

IIIa heavily damaged stand 50 IIIb very heavy damaged stand 70 IV dying and dead stand 100

Decree No. 78/1996 Coll., Ministry of Agriculture

In some countries abroad (Germany, Poland) similar access to damage classification on ecosystem (stand damage) started to be advocated in the past years, mainly in a context with international research of the distant survey methods for damage classification. Satellite imagery use resulted to be useful. See

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Large Area Experiment for Forest Damage Monitoring in Europe Using Satellite Remote Sensing - LAOE, UNEP/Regional Office for Europe, , 1990 – 1996, in which participated Poland, Germany, Sweden, USA, and the Czech Republic. The Czech Republic, represented by the FMI and by the STOKLASA Tech. Praha, was the leading country in that experiment.

In Germany, decisive criterion in management method choice has been the damage degree of one tree. This strategy failed in the 1990´s after climatic extremes: temperature inversions followed by extreme high pollutants concentrations.

It is necessary to mention one significant disadvantage of the Czech stand damage classification system, which reduces its applicability in satellite imagery classification. For to be easily understandable, the scale is based on the presence of heavy damage and does not calculate with damage intensity of the other trees. These can be damaged by the IInd degree or by the Ist degree, without the stand damage degree change. Of course, that change is reflected by the satellite image, causing distortion of classification. For this reasons, the Czech classification has been modified, showing now the average defoliation of all the trees within a forest stand. Such a classification would be more difficult in the field and the original scale use is recommended there.

1.3 Air Pollution Threat Zones to forest

Air Pollution Threat Zone is a region where the average rapidity of forest stand

damage degrees /3orway spruce, 100 years of age) deteriorate within defined

intervals..

Air Pollution Threat Zones theory was created by the FMGRI Jíloviště-Strnady in 1958 (Materna, Samek, authors´ statement) in the same time as the other scales were and the system is in use up to now. An idea to evaluate not only the damage status, but also dynamics of it, enabled wide practical applicability of acquired data on health status of the Czech forest in forest management planning. Ecological catastrophe 1978/1979 occurred suddenly and in the time, when no sufficient experience and information how to face the situation, has been at disposition. The system possibilities experience transfer and applicability among various natural regions and localities inside them. Experience coming from the pollution affects has been also applied in the case of Ophiostoma fungi (tracheomycosae) outbreaks in the middle 1980´s.

There are four of the Air Pollution Threat Zones (A to D, where A is the most endangered one). Originally, a zone without damage has been mapped before 1986. Because of the damage occurrence within quite all the Czech forests, since that the zone D is delimited everywhere, where higher zone is not evaluated.

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At first, the zones were defined by the pollution load, relation being derived from the Krušné (Erzgebirge) Mts., North Bohemia. Life expectancy of the forest stands was assessed as a function of the average annual concentration of the SO2. After the 1978/1979, the damage spread onto all the mountain ridges along the northern borders of the Czech Republic and it became clear, the relation depends more on regional site and climate conditions than on the pollution concentration. Since that time, this definition insisted in damage dynamics only.

Table 3. Pollution threat zones to forests

(�orway spruce mature stands)

Threat zone

Stand damage degree increase in the course of 10

years

Upper limit of the

zone

Maximum life

expectancy

minimum maximum rounded stand damage degree years**

A 2,00 >2,00 < 20 B 1,00 1,99 2,0 20 C 0,67 0,99 1,0 40 D (0,50) 0,66 0,7 60

Note: ** since the beginning of the pollution impact Decree No. 78/1996 Coll., Ministry of Agriculture

Idea of Air Pollution Threat Zones had not any analogy abroad (East Germany, Switzerland, Poland). These countries usually mapped the damage status in one distinct moment and change of the status was described only comparing maps made in different time. Monitoring has not been systematic and localities were monitored ad hoc. Forest stands were managed according to the momentary health status and accidental weather effects could cause problems in management conceptions. The management consisted in felling dying and dead trees and in reforestation of gaps with tree species selected under local opinions.

Air Pollution Threat Zones do not loss its value notwithstanding the pollution amount reduction. The Zones indicate localities susceptible to endogenous negative influence to forest ecosystems and contain permanently important information also for the future.

The zones were gradually mapped by three teams from the FMGRI Jíloviště-Strnady and by the forest protection specialists at branch offices of the FMI. In 1995 an objectification and upgrade of the maps has been done.

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2 Methodologies of the Air Pollution Threat Zones upgrade 1995.

2.1 Groundwork

The pollution damage to forests classified on the LANDSAT TM-5 imagery by STOKLASA Tech. Praha before the year of 1996 has been used. Time series 1984-85, 1986-88, 1990-1992 a 1993-94 of classified maps of damage and mortality were disponible. Classification was done according to the Czech damage classification scale. Individual maps covered entire area of the Czech Republic but small area of Aš region in the NW corner, a small part of neighboring scene which was not brought for the lack of money.

Applied was the Methodology of delimitation (Metodika vylišování pásem

ohrožení lesních porostů v oblastech zatížení imisemi, Materna, 1989) obtained from the FMGRI at 30.8.1989. According to this Methodology, the Zones should delimit life expectancy of mature Norway spruce forest stands starting with the beginning of the pollution affect and ending with the stand disintegration. Forecast of life expectancy in years is to be evaluated by following methods:

• By extrapolation of the hitherto development

• Assessing it from experience in relation with air pollution load and damage

• Assessing not only the pollution effect but including also other mechanism affecting the health status

The first process has been chosen: an extrapolation of damage change curve in the past. Standard definition of the Zones from the Ministry of Agriculture Decree 78, 1996 Coll. (developed in the FMI) was applied: „the Zones should be delimited according to the average size of damage degree decline of a Norway spruce stand in one decade”.

2.2 Objectification and upgrade methodology

Following principles as the base for the Air Pollution Threat Zones were formulated: (Závěrečná zpráva revize, ÚHÚL, July 1997):

• Practical usability and applicability of the Zones is really proven yet. Problems inhere in disunity of the work done by numerous assessors and methodologies change in the past. In some regions, delimitation had been executed before the damage symptoms were clear

• The revision aims to objectification and coordination of the Zones delimitation, and Zones upgrade in accordance with the present development. It does not aim to complete new delimitation.

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• The Air Pollution Threat Zones are an evaluation of visually recordable effect of synergetic influences very variable and unspecified number of factors and conditions on variety forest tree species growing onto very variable site conditions, soil properties as well as climatic factors. Also genetic properties of tree species and individual trees among them (predisposition, resistance, and resilience to exogenous factors) can differ even between neighboring individuals. It means, the ecosystem access is to be used in damage evaluation. Borders between the zones are not line hybrids; these are belts where the characteristic changes gradually. Size of such a belt oscillates from a few meters (sharp slopes) to some hundreds meters (plain terrains). The zones cannot be delimited fully exactly; prevailing data should be the base for the Zones delimitation between localities that can be mapped unambiguously. That time acceptable SW and digitized maps of the Czech Republic were not yet at disposition. So, any manual work bringing some risk of subjective errors cannot be fully delimited. More acceptable is the systematic error than the accidental one. With regard to aimed application of the Zones (future development of damage assessment, differentiation of management methods in individual forest stands, bioindication of the pollution load) the disadvantages mentioned above do not limit the applicability of Zones.

• For the quality improvement of the Zones usability, an objective classification of the damage in the Norway spruce forest stands on time series of Landsat TM-5 satellite imagery is used.

• A selective characteristic for the images applicability is the persistence of detected damage changes within the image series since 1984.

• Given by specific properties of the imagery, use of ground collected data is inevitable, These (stand age, species composition, stand density) are contained in the database of forest management plans, where every Czech forest stand can be found. Also backup or/and testing field survey is needed (Häusler, 1995).

• Land without Norway spruce stands or areas, where that stands were cut down before 1990 is localized inside the Zones A and B (see the Zones definition). Limits of these Tones have been delimited and twice or three times rectified in the field and do not demand complete evaluation. However, testing is desirable.

• There is not any trustworthy criterion indicating borders between Zones D and 0. The period of the pollution influence is not sufficient for reliable permanent pollution caused damage proof. All the forests, which do not show a damage corresponding to the Zone C, minimally, lie in the Zone D.

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• Borders of the Zones usually do not follow borders of the forest management units (compartments, stands) or the borders of cadastral districts. (However, in 2002, this principle has been abandoned on a request of the Ministry of Finances for to the tax breaks could be granted more simple: smaller forest stands were evaluated by the zone prevailing on the forest area). Mapping accuracy is given by the 1:50,000 scale of base maps (1 mm equals to 50 ms in the field) and by the size of picture elements (pixels) in the imagery (30 * 30 ms), taking in the mind the pixel dereferencing possibility and the fact, that pixels in different scenes of the same region are not identical in the field. Described imagery properties limit the classification to land lots with size of 100 ms and the delimitated Zone size to about 100 hectares. Smaller area can be tried to delineate in ecologically important cases (mountain tops and so on).

• For statistical reasons, the Zones should be closed polygons. In areas out of forest, borders should be assessed.

• Subjective evaluation will be reduced by the „one eye“ method. One responsible assessor should finalize the maps.

Similar principles are desirable to be followed also in next upgrades.

2.4 Data and information processing

The works on the Air Pollution Threat Zone revision and upgrade were started at the beginning of the 1996 and have four phases:

• (1) Preliminary delimitation of the Zones on the base of satellite scenes classified by STOKLASA Tech.

• (2) Data collection from the field in areas with small forest lots and rectification of the preliminary maps

• (3) Delimitation and reliability proposal control by the local specialists

• (4) Final map construction on the scale of 1:50 000

2.4.1 Preliminary delimitation of the Air Pollution Threat Zones on the base of processed satellite imagery

Accessible common organization maps on the scale of 1:25 000 and the forestry maps on the scale of 10 000 showing forest stand age classes, both designed by the FMI, served as the evaluation base. These maps were copied to the scale 1:50 000.

Classified satellite images mostly from the years 1992 or 1993 were printed on the same scale. Accessible were also scenes from the past in prints or on the computer.

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Tables of damage degree change rapidity by stand ages and different periods of pollution influence make an important tool of satellite imagery classification implementing into process.

As any SW capable process the maps digitization as fast as it was necessary was not available, following step was done using tracing paper. Apparent borders of the Zones were evaluated from the classified images to the overlay. The image classification must be interpreted for to obtain accurate information because the image (reflectance) is affected by the tree species (pine seems to be more damaged spruce), tree age (damage of a young stand is a symptom of higher Zone than the same damage degree on a mature stand), and transparency of the crown (the reflectance if heavily influenced by the vegetation on the forest stand floor).

For this reasons, promotive field data (age class, species composition and stand density) were applied found in appropriate forest management plan. Rectification of the apparent borders to probable borders of the Zones was done on the base of that information, resulting in preliminary delimitation of the Zones.

2.4.2 Air Pollution Threat Zones delimitation process in small forests

In regions with minute and prevailing mixed forest, where the interpretation of a classified satellite image is very difficult because of the frequent presence of „false pixels“ (picture elements hard or even impossible to be classified for covering different ground vegetation cover, for example road and forest trees), field information has been applied.

A correction of preliminary borders of the Zones has been done on the data from the 1,130 temporary sample plots (reference points), mainly located in lowlands or hilly regions. These points were localized by GPS, and located and drawn into maps.

In military forests, Zone borders delimited before have been copied.

In localities without forest, Zone border has been assessed (to be used case the land will be afforested in the future).

2.4.3 Proposal of the Zones delimitation

Final rectification has been done by the FMI specialists at regional branch offices.

The first proposals were corrected or accepted. In period from September to November, 1996, field trips were executed at presence of local specialists and the advisor of the project. They decided any problem or question inside the forest in focus. Important and mostly the decisive information about damage change trends persistence was found in the classified satellite imagery.

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Majority of mistakes was caused by low density of stands, too mixed composition, and stands just after thinning, where the damaged trees were extinct.

Results of the process have been gradually digitized and stored in the official Forest Management Plans Database.

2.4.4 Final delimitation of the Zones

Final mapping of the Air Pollution Threat Zones has been executed by a transplantation of the correct Zones borders into official analog maps of the Czech Republic on the scale of 1:50 000 brought at licensed stores of the Czech Institute for Geography and Cartography. Fair copy was done manually.

The maps (every sheet) were approved by the Ministry of Agriculture. One set of these maps has been saved at regional governments as the official version of the Air Pollution Threat Zones in the Czech forest. In total, 564 sheets of the first map copies have been produced.

Fig. 1. Air Pollution Threat Zones to forest

Second and the third copy has been stored at the FMI´s archives and served as register and record of further corrections. In the course of the past 14 years, small corrections have been needed, mainly cancellation of small areas of the Zone C.

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Map images on various scales have been processed from the digitized data. After digitization of the entire area of the Czech forest in detail (basic maps on the scale of 1:5 000, average size of the forest stand detail about 0,25 hectares), also the Zones borders have been digitized in this scale enabling to add the Zone to every land lot in the official land records (cadastre).

3 The Air Pollution Threat Zones application into forest management planning

3.1 Zone use in forest management

• Decision on regeneration urgency: more urgent is the regeneration of the forest stand which will die faster.

• Decision on the beginning of regeneration: large in area forest stands, where dying is expected in near future, are to be regenerated not considering their age. The aim is to have the regeneration started or half done at the stage of the forest decline en mass. It is necessary to have some stand of second generation established for to eliminate occurrence of large cleared localities without forest. Such clear-felled areas are hard to be reforested any way according to the experience from the Krušné Mts. pollution caused disaster.

• Decision on fitness and method of thinning: there should be enough time for to the stand can react to the costly care. Increment gets lowering proportionally to the stand damage degree and time needed for the stand reaction to the thinning lengthens out. Removal of dead trees is proper when the wood will be saved and the stand will not be endangered more than it is. In the late stage of the stand decline, regeneration of the entire area is better, because the microclimate positively influenced by the dying and dead trees will be approved for plants.

• Decision on the new stands tree species composition: ecologically appropriate domestic species should be planted in localities with lower pollution load. In heavily affected localities, any tree species able to withstand the conditions must be used. The so called substitution stands will have low or even none wood production but they will save the non-productive forest functions, forest soil properties, and local climate conditions.

• Decision on the forest reconstruction beginning: substitution stands formed mostly from introduced tree species should be gradually transformed into ecologically and economically optimized site

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appropriate mixtures of tree species as soon as the pollution load will be abolished. The reconstruction should not start too soon and the process should be stretched into several decades for to new uniform and even aged stands will not be created.

• The Zones show localities very probably more susceptible to exogenous and endogenous negative affects where permanent full attention must be given to forest protection.

4 Web application of the Air Pollution Threat Zones

(See URL http://geoportal2.uhul.cz/mapserv/php/mapserv3.php?project=landsat&

4.1 Contemporary content of the web application

Web application based on Mapserver and supplied by the WMS and CSW makes it accessible the following unique information from the satellites LANDSAT TM (time series 1984-2007) in the form of the seamless map composition within entire area of the Czech Republic:

A – Damage and mortality in forest stands (Czech scale)

B – Defoliation and mortality of coniferous forest stands (10 % defoliation scale)

C – Development of the damage and mortality in coniferous stands

D – Threat to the coniferous stands

E – Coniferous forest health decline trends

4.2 Technological background of the classification

• “Damage degree and forest stand mortality”, is based on the Czech classification system of damage to coniferous stands (forest stand damage degrees 0, 0/I, I, II, IIIa, IIIb, IVa, IVb). Loss of needles is the decisive criterion in this scale. In some cases, also the status of the needles (discoloration) plays role in the damage degree determination. Such parameters are close to the information available from the satellite images which characterize the health status of forest trees and damage intensity.

• “Defoliation and forest stand mortality” is classified using the ten-percent-interval classification scale which shows following defoliation degrees: 0%, 1-10%, 11-20%, 21-30%, 31-40%, 41-50%, 51-60%, 61-70%, 71-80%, 81-100 %. Average defoliation of all trees on one pixel

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area. This scale gives smarter differentiation of the damage classification and better fits the defoliation within a real forest stand. However, it is much harder to be assessed in the field.

Application fully fits the I�SPIRE and GMES principles • FMI, a governmental institute supervised by the Ministry of Agriculture

annually assures upgrade of the data series according to the Ministry of Agriculture Decree no. 78, 1996 Coll.

• Source data are owned by the Ministry of Agriculture

• The application exploits and shares another servers of other organizations as basal data sources

• The application has been prepared for the implementation into the metainformation system MICKA, which fully supports the 19115 standard

• The application makes use of web services (WMS)

Application benefits

• The application enables a forest owner to evaluate his tax breaks more

objectively delimiting borders between different taxing characteristics. • State institution and supervision organs in forestry have instant

information when any situation occurs not expected before (forest health status monitoring, compensation of damage, damaging agents outbreak centers identification).

• Objective information is available useful or needed for environmental monitoring and studies.

• Objective control mechanism of activities focused to environment improvement is at disposition.

Application use inside the Czech Republic and in abroad

The application accesses seamless map composition covering whole area of the Czech Republic in a sufficient resolution (picture element size 30 * 30 meters). The application enables evaluate air pollution damage to forest effects and also to evaluate long-term and short-term damage development and to formulate trends and prognoses.

Such information is important in forest management planning and execution.

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5 Findings

After the Air Pollution Threat Zones revision 1996, the Zones were considered to be definitely mapped. Extreme inversion situations which occurred later have shown that the threat is not totally eliminated. Also the other negative influences till then overlapped by the pollution affect alighted from on the light.

With pollution amounts great reduction in the course of 1990´s and in the first years of this century, affect of the influence other than pollution is more clear and should be included into decision process in Forest management planning. Zones upgrade need was postulated by various scientists and institutions.

This upgrade of the Zones has the following premises:

The Zones importance does not disappear. It is the chronic damage to be faced by the forestry now. The Zones show a relative local vulnerability level which is given not only by the pollution load but also by site qualities, climate properties, and partly by endogenous influences.

Deciding information on individual forest stand should be more complex, i.e. additional data on site conditions should be added to the Air Pollution Threat Zones-

Tools aimed to this demand satisfaction should be searched and developed as soon as possible.

In answering this demand, the future Forest Risk Zones are defined as the categories which substitute the Air Pollution Threat Zones used up to now in accordance with the Ministry of Agriculture Decree no. 78, 1996 Coll.. The new Risk Zones are conceived also as the base for subsidies policy in the forestry. Risk Zones are delimited on the base of multicriterial analyses which uses a variety of data stores and sources. These sources contain statistical data on forest health status obtained by the means of distant methods of forest surveys and by the forest soil regionalization according to its acidification and nutrition decline (degradation). Proposed are three Risk Zones in following categories:

1 – Low risk

2 – Medium risk

3 – High risk.

The Risk Zones sense is to integrate the Czech forest site typology methods with a methodology of forest protection and to form a new platform for the multicriterial evaluation of forest health status with practical outputs to the fields of silviculture, treatments, care, and amelioration. An important part of the project .consists in demarking of acute and chronic decline of forest stands.

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So the project is partly focused also to a proposal of a new system of forest soils regionalization according to the acidification and nutrition degradation.

The system would be proposed for the entire Czech Republic, covering whole variability of forest natural regions and must be based on health decline analyses. The Risk Zones will substitute the role of contemporary Air Pollution Threat Zones in forest management planning and state governmental politics in forestry.

Outputs of the project will be processed so, to they enable implication into the forestry law (still in preparation) and replace the Ministry of Agriculture Decree no. 78, 1996 Coll. .

Outputs will be presented in the GIS environment and the new system of forest regionalization will enable to interconnect it with other forest thematic maps including standard forestry maps.

Within the FMI, the project is warranted by the Frýdek-Místek branch office.

References

1. Häusler, Th., ed., 1995: Forest Damage in Central European Mountains, Final Report of a Large Area Experiment for Forest Damage Monitoring in Europe Using Satellite Remote Sensing, UNEP/ROE, Geneva.

2. Henžlík, V., 1987: Závěrečná zpráva etapy 13 „Podklady pro směrnice režimu těžeb a dodávek imisemi poškozeného jehličnatého dřeva“, in: Závěrečná zpráva výzkumného úkolu RVT P 17-322-823 „Využití dřeva poškozeného imisemi“, koordinátor F. Jirků, VVÚD Praha. (in Czech)

3. Henžlík, V., 1989,1990: Seriál krátkých textů s obrazovými tabulemi o hodnocení poškození jednotlivých dřevin a porostů a o využití DPZ ke klasifikaci poškození, Lesnická práce 1989 (1, 2, 5, 6, 7, 8, 11, 12) a 1990 (1, 2, 5, 6, 7, 8, 11, 12). (in Czech)

4. Henžlík, V., 1991: Klasifikace poškození lesů antropogenním znečištěním ovzduší, Lesprojekt, Brandýs n. L. (in Czech)

5. Henžlík, V., Stoklasa, M., 1995: Pilot study on the assessment and monitoring of forest damage in selected areas of the Czech Republic, ÚHÚL Brandýs n.L., Stoklasa Tech. Praha.

6. Henžlík, V., 1996: Revize pásem ohrožení lesů imisemi, Technická zpráva, ÚHÚL Brandýs nad Labem. (in Czech)

7. ICP-Forests, 1992: Forest Condition in Europe, Report, CEE - UN ECE, Brussels, Geneva, p. 5.

8. Kučera, B., 1979: Podíly stupnů poškození jedince ve stupních poškození porostu. Manuscript. (in Czech)

9. Materna, J., 1958: Klasifikace poškození lesních porostů. Práce VÚL, VÚLHM, Jíloviště-Strnady. (in Czech)

10. Materna, J., 1973: Klasifikace ploch lesních porostů zasažených imisními vlivy stanovením pásem (zon) ohrožení s uvedením systému jejich vylišování. VÚLHM. (in Czech)

11. Materna J., 1989: Metodika vylišování pásem ohrožení lesních porostů v oblastech zatížení imisemi, Manuscript. (in Czech)

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12. Metodický návod (1980) k vylišování pásem ohrožení čj. 31349/ORLH-148/ODV/80 (Věstník MLVH ČSR, ročník 1980, částka 20-21). (in Czech)

13. Metodický návod (1988a) k vylišování stupňů poškození čj. 31348/ORLH-148/ODV/80 (Věstník MLVH ČSR, ročník 1980, částka 20-21 (in Czech)

14. Metodický návod (1988b) pro klasifikaci poškození lesních porostů imisemi MLVH ČSR čj. 26 269/ORLH/169/ODV/87 (Věstník MLVH ČSR, ročník 1988, částka 5 - 6) (in Czech)

15. Plíva, K. et al., 1991: Funkčně integrované lesní hospodářství, vol. 3, Modely hospodářských opatření, ÚHÚL, Brandýs n. L. (in Czech)

16. Pospíšil, F., 1979: Záznamy periodického hodnocení poškození stromů na zkusných plochách. Manuscript. (in Czech)

17. Příkaz č. 7 náměstka ministra k postupu obnovy lesních porostů postihovaných exhalacemi, MLVH ČSR čj. 31353-ORLH/153-ODV/80 ze dne 12.1.1981 (in Czech)

18. Stoklasa, M., 1997: Nabídka map zdravotního stavu lesů z kosmických snímků, Stoklasa Tech., Praha. (in Czech)

19. Strain, P., Engle, F., 1992: Looking at Earth, The National Air and Space Museum, Smithsonian Institution, Washington, D.C., Turner Publishing Inc., Atlanta, U.S.A.

20. Tichý, J., 1988: Křivky zastoupení stupňů poškození jedince ve stupních poškození porostu, výsledky monitoringu na zkusných plochách VÚLHM. Manuscript. (in Czech).

21. Vyhláška č. 78/96 MZe ze dne 18. 3. 1996 o stanovení pásem ohrožení lesů pod vlivem imisí. (in Czech)

22. Westman, L., 1990: Variables for assessment of birch, beech, and oak, Instruction for assessing damage to..., Institute for Ecology and Botany, University of Umea, Sweden. Manuscript.

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Conclusion

Karel Charvat

The book “INSPIRE, GMES and GEOSS Activities, Methods and Tools towards Single Information Space in Europe for the Environment” used finished and running European projects to demonstrate the possibilities of integrating INSPIRE principles with GMES and GEOSS initiatives. The book covers all parts of data management, observing and analysis.

In the direction of SISE implementation the presented papers addressed following topics:

1. SISE Context • Complexity Management

2. Application/Services • SISE Services

• Process Chaining & Uncertainties

• Real-time Mapping & Modelling

• Thesauri

• Open Standards & Open Source Software

3. SISE Open Semantics & Standards • Standardisation & Framework Projects

• Standardisation & Community Knowledge

• Semantic Web Technologies for the SISE

• Ontologies

4. Data Interoperability &Web Communities • Web 2.0 Technologies

• Data Provision in the Semantic Web

• SOA/Web Services & Model-Driven Communities

• Social SISE

5. Data Visualisation & Modelling including Risk Assessment • Visualisation of Environmental Data

• SOA & Semantic Web Services

• Simulation & Modelling

• Complex 3D/4D Models

• Chained Web Services & Legacy Systems

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6. SISE Deployment Models • Regional Application of European Interoperability Standards

Due to the number of aspects of SISE discussed in this book, the material can be considered a demonstration of feasibility of future SISE implementation.

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