DESIGNING WEB-ENABLED SERVICES TO PROVIDE DAMAGE ESTIMATION MAPS CAUSED BY NATURAL HAZARDS Turin-Italy 2010

DESIGNING WEB-ENABLED SERVICES TO PROVIDE DAMAGE ESTIMATION TO PROVIDE DAMAGE ESTIMATION

MAPS CAUSED BY NATURAL HAZARDS

F. V. Gutierrez, M. A. Manso, M. A. BernabeD H Lang M Wachowicz W StrauchD. H. Lang, M. Wachowicz,, W. Strauch

CONTENTCONTENT

1 Introduction1. Introduction2. Related work 3. Case of study4. Methodology5. Results6. Conclusions and future work

1. INTRODUCTION (2) The need for a map

? ? ?? ? ? ? ?

?                    ?          ?              ?                   ? ??                         ?   

A map for answering questions related to: location, casualties, damage zones

1. INTRODUCTION (3) The answer can depend in the level of detail of the base information.

A big granularity:

the level of detail of the base information.

A

(example)Cities :- The number of people

B

A - The number of people - Amount of houses.

CBut when attempting to predict and estimate losses due to natural hazards

f- Demographic information- Buildings stock inventory- InfrastructuresInfrastructures

1. INTRODUCTION (4) Problems when reaching this kind of information:this kind of information:

- Information is related with protected information.Information is related with protected information.- Created for taxes goal not thinking in Risk.- There a large numbers of initiatives promoting SDI but only in a

few cases natural hazards domains is included into them (Schmitz et al.), that's mean s that if the information is available it is no often through out standardized way for software accessingoften through out standardized way for software accessing

1. INTRODUCTION (5)

THE CHALLENGETHE CHALLENGE- Analysis and design of a set of OWS using

the available resources, as promoted by SDI initiatives.- Identification of services to reproduce the experience in other

places.

THE MOTIVATIONTo propose a distributed and standardized visionfor providing data access and information processing for estimationfor providing data access and information processing for estimation and presentation of the damage caused by natural hazards.

2. RELATED WORKThi i h 't b h i

PAGER: Prompt Assessment of Global Earthquakes for ResponseDeveloped by the USGS

This review hasn't been comprehensive

Evaluates the number of people, cities and regions exposed to a powerful earthquake in all over the world.

Developed by the USGS.

2. RELATED WORK (2)

2. RELATED WORK (3)

Why doesn't PAGER estimate loss of life or property?in order to estimate building damage or human casualties, it would be necessary to use databases of building inventories...No such database exists on a global scaleto use databases of building inventories...

2. RELATED WORK (4)

GEM: Global Earthquake ModelIntends to be an independent, consistent standard of worldwide application for calculation of risks, estimate of loss by an earthquake and communication of hazards. (2013 the first complete global earthquake model).

2. BACKGROUND (5)

CAPRA: Central America Probabilistic Risk Analysis

CAPRA is defined as an information platform to support risk management for decision making in natural disasters.

i l t O G N d- implements OpenGeoNode- Uploading of data and metadata in the GeoNode- OGC standardized services WMS, WFS and CSW

- Lack of direct connection to the data sources.

3. CASE OF STUDYHazards:EarthquakesLandslidesLandslidesEruptionsTsunamisHurricanesFloods

NICARAGUA

hit by 3 powerfulManaguahit by 3 powerfulEarthquakes In the20th century, last one left

h lf f l tione half of populationHomeless.

3. CASE OF STUDY (2) Agencies/Resources

Two studies of seismic risks and vulnerability of Managua had been carry out in Managua since 2003. The last one in 2009 (RESIS-II).

Agencies ResourcesM B ildi St k I tManaguamunicipality

Building Stock Inventory.

INETER Hazard information in GIS formatINETER Hazard information in GIS format.INETER Near-Real-Time earthquake information.NORSAR Software for Risk and Loss estimation.NORSAR/UPM Software for Risk and Loss representation.UPM/NORSAR Software for assigning typology to the

b ildibuildingsUPM Geo-Web Services Chaining

3. CASE OF STUDY (3) Resources for loss estimations due to Earthquakes (DATA)

1. Seismicity database: Historical event database.

due to Earthquakes (DATA)

1. Seismicity database: Historical event database.

3. CASE OF STUDY (4) Resources for loss estimations due to Earthquakes (DATA)due to Earthquakes (DATA)

2. Soil classification : Created from the study of analysis and2. Soil classification : Created from the study of analysis and response spectrum of the soil in different city areas.

3. CASE OF STUDY (5) Resources for loss estimations due to Earthquakes (DATA)due to Earthquakes (DATA)

3. Information of the event (Earthqueke): Detected, processed and sent to the seismic station through the Earthworm and Seisanand sent to the seismic station through the Earthworm and Seisansystems.

3. CASE OF STUDY (6) Resources for loss estimations due to Earthquakes (DATA)due to Earthquakes (DATA)

4. building stock inventory : Obtained from SISCAT, the municipal4. building stock inventory : Obtained from SISCAT, the municipal cadastre system of Nicaragua. This database contains over 200,000 constructions.

3. CASE OF STUDY (7) Resources for loss estimations due to Earthquakes (Model)

5. SELENA: SEismic Loss EstimatioN using a logic tree Approach.

due to Earthquakes (Model)

5. SELENA: SEismic Loss EstimatioN using a logic tree Approach.

... allows calculating the damage as a function of the available information sources and levels of uncertainty associated to input data ..

3. CASE OF STUDY (8) Resources for loss estimations due to Earthquakes (Softwares)due to Earthquakes (Softwares)

4. METHODOLOGY

For designing the proposal a system architecture the followingsteps were done.

1) Analysis - Earthworm and Seisan) yfor implementing services of warning and notifications.

2) S d B ildi l i Al i h /P2) Study - Building typologies Algorithms/ProgrammesResistance capacity curves / building of the inventory.

3) Study - SELENA APIfor publishing their functionalities with OWS.

4) Analysis - SELENA Input/Ouput

4. METHODOLOGY (2)

5) Analysis – RISeRISe APIfor publication of its functionalities in a standardized way.

6) Analysis - RISe input /output

7) Data harmonization (building inventory ) for the cadastraldata base.

8) Modelling of the sequencing and arrangement of the execution8) Modelling of the sequencing and arrangement of the executionof services published for processing and warning on the basisof the available data.

9) Design of a system architecture connecting all standardizedresources through the Internetresources through the Internet.

5. RESULTS

Resources OGC standards Relationship name1. Soil classification2 Construction inventory database

WFS, GML, WMSWFS GML WMS

SC-WFSCIDB WFS2.Construction inventory database WFS, GML, WMS CIDB-WFS

3. Building typology database WFS, GML BTDB-WFS4. Assignment of structural vulnerability information to

WPS, WFS, GML AV-WPSAV-WFSvulnerability information to

building typologies AV WFS

5. Seismicity database WFS, GML, WMS SDB-WFS6. SELENA WPS SELENA-WPS. S6.1 SELENA input data6.2. SELENA output data77.. RISeRISe

W SWFS, GMLWFS, GMLWPS

S W SSELIN-WFSSELOUT-WFSRISE-WPS

77..11 RISeRISe input data77..22 RISeRISe output data8. Earthworm

WFS, GML, KMLWFS, GML, KMLSAS, WNS

RIN-WFSROU-WFSEW-SAS-WNS

9. Seisan SAS, WNS SS-SAS-WNS10. Geoservices arrangement(Orchestration engine)

BPEL (not an OGC standard )

OREN-BPEL

5. RESULTS (2)

5. RESULTS (3)

6. CONCLUSIONS AND FUTURE WORK

1. The main contribution of our work has been the proposalstandard geoservice architecture to generate damagestandard geoservice architecture to generate damageestimation maps from seismic events.

For the design of these services we have tried to reuse to theutmost existent resources..utmost existent resources..

6. CONCLUSIONS AND FUTURE WORK (2)

2. The application of standardized technologies to interconnectautonomous systems ensures their interoperability.y p y

3. The proposed architecture keeps the roles of actors/agenciesand people.and people.

4. An issue that will require a coordination effort is data modelspecification to be offered by the municipalities with thecadastral data.

5. The use of geo-referenced syndicated news (GeoRSS) for tupublish the seismic events.

The end

Thank youThank [email protected]@topografia.upm.es