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Matriculation number:
1
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Examination Assignment
Module: Geoinformatics
Exam part: Geoinformatics
Examiner: Prof. Dr. Leuchter, Dipl.-Biol. Ralf Darius
Deadline for the submission: 07.02.2016, 11:59 pm
Study program Begin of studies Last name, First name
Information Winter
Semester,
Engineering and Nawaz, Muhammad Ahsan
Computer Science 2015/16
(M.Sc.)
Assessment criteria and number of points that can be achieved:
Maximum number of GIS skills Systematic and Quality of the Presentation of
points scientific Quality results the results
100 45 15 30 10
Result:
Points Mark GIS skills Systematic and Quality of the Presentation of scientific Quality results the results
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Hochschule Rhein-Waal
Rhine-Waal University of Applied Sciences
Faculty of Communication and Environment
Prof Eng. Ralf Darius
Term Paper
Winter Semester 2015/2016
Module “Geoinformatics”
A Report Submitted in
Partial Fulfillment of the
Requirements of the Degree of
Masters
In
Information Engineering & Computer Science
By
Muhammad Ahsan Nawaz
Matriculation Number:
18790
Submission Date: 05/02/2016
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Statement of Authorship
This report is the result of my own work. Material from the published or unpublished work of
others, which is referred to in the report, is credited to the author in the text
Name: Muhammad Ahsan Nawaz (18790)
Signature: Ahsan
Date: 05.02.2016
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Table of Contents 1. Introduction ....................................................................................................................................... 3
2. Tools & Methods ............................................................................................................................... 4
2.1. GIS .............................................................................................................................................. 4
2.2. QGIS ........................................................................................................................................... 4
2.3. OSM............................................................................................................................................ 4
2.4. NDVI ........................................................................................................................................... 5
2.5. CRS ............................................................................................................................................ 5
2.6. GRASS Plugin: .......................................................................................................................... 5
3. Tasks ................................................................................................................................................. 6
3.1. Task 1 ......................................................................................................................................... 6
3.2. Task 2 ......................................................................................................................................... 7
3.3. Task 3 ......................................................................................................................................... 9
3.4. Task 4 ....................................................................................................................................... 10
4. Discussion of results ...................................................................................................................... 12
References .......................................................................................................................................... 13
List of Figures:
Figure 1: Task 1 ------------------------------------------------------------------------------------------------------------------------ 7
Figure 2: Task 2 (1) ------------------------------------------------------------------------------------------------------------------- 8
Figure 3: Task 2 (2) ------------------------------------------------------------------------------------------------------------------- 8
Figure 4: Task 3 ----------------------------------------------------------------------------------------------------------------------- 10
Figure 5: Task 4 ----------------------------------------------------------------------------------------------------------------------- 11
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1. Introduction
Geoinformatics is the art and science of storing, measuring, visualizing, organizing and
analyzing the data related to the phenomena occurring on or near the earth‟s surface.
Geoinformatics combine geospatial analysis, modeling, geospatial databases, human-computer
interaction and both wired and wireless technologies to analyze information related to earth. Its
applications are in several fields such as urban planning and land use management, tourism,
virtual globes, environmental modeling and analysis, transport network planning and
management, agriculture and telecommunications. Global navigation satellite systems,
cartography, geographical information systems (GIS), geodesy, remote sensing and web
mapping are also branches of geoinformatics.
Global navigation satellite system is a system of satellites that delivers autonomous geo-spatial
positioning with global coverage. Cartography is the study and practice of creating maps.
Geographical information system is a system that captures, stores, analyzes, manages and
presents data with reference to geographic location data. Geodesy is the scientific discipline that
deals with the measurement and representation of the Earth. Remote sensing is a common branch
of geoinformatics. It is the acquisition of information about an object or phenomenon, without
making physical interaction with the object. Web mapping is the process of designing,
implementing, generating and delivering maps on the World Wide Web. [1] [2]
This project comprises four tasks and it is done using QGIS (quantum geographic information
system), which covers compilation of 12 personal impressions and locations of Kamp-Lintfort
and integrating those personal geographical representations of Kamp-Lintfort into a GIS
(geographic information system) data model. Then, on the basis of OSM (open street map) data
in the map, the shortest route among those 12 places is recorded. Afterwards, NDVI (normalized
difference vegetation index) is calculated with the help of raster data and finally the ROI (regions
of interest) are marked on the myKamp-Lintfort map data set using semi-automatic classification
plugin.
1.1. Objective
The main objective of this report is to maximize the efficiency of decision making & planning.
This report provides efficient means for data distribution & handling. The main purpose of this
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report is to eliminate of redundant database-minimize duplication. It has a capacity to integrate
information many sources. Complex analysis/queries involving geographical reference data to
generate new information. GIS can update data quickly & cheaply. The main objective is to aid
in the protection, preservation & interpretation of the cultural & natural resources of the park.
GIS is to provide information useful to the General management plan & future projects.
2. Tools & Methods
Following tools & methods were used to accomplish the final assessment task.
2.1. GIS
A computer system used for capturing, storing, checking and displaying data related to positions
on Earth‟s surface. Geographic information system (GIS) can demonstrate various sorts of
information on one map. This empowers individuals to effectively see, examine and comprehend
patterns and relationships in the data. In addition GIS gives the ability to make maps, incorporate
information, envision situations, exhibit capable thoughts and create effective solutions. GIS is a
tool utilized by people and associations, schools, governments, and organizations looking for
imaginative approaches to tackle geospatial related problems.
2.2. QGIS
QGIS (QGIS) is an open source, community driven Geographic Information System (GIS) that
runs on Linux, Windows and Mac „OS‟. The desktop GIS offers organizations a real alternative
or supplement to otherwise expensive vendor based licensing. QGIS is a fully functioning
desktop GIS and includes all the features that spatial professionals and general users would
expect such as importing data from multiple sources, digitizing, editing, on the fly projection,
data analysis, reprocessing, database connectivity and raster processing. The highly capable print
layout functionality is intuitive and easy for new users to create professional looking maps.
Delivering comprehensive functionality, ease of use and a collaborative user community, QGIS
is the ideal solution to address all your desktop GIS requirements.
2.3. OSM
Open street map (OSM) is a communitarian project to make a free editable guide of the world.
Two noteworthy main thrusts behind the foundation and development of OSM have been
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confinements on utilization or accessibility of map information crosswise over a significant part
of the world and the coming of cheap versatile satellite navigation gadgets.
2.4. NDVI
A straightforward graphical indicator that uses the visible and near-infrared bands of the
electromagnetic spectrum, and is adopted to analyze remote sensing estimations, normally
however, not so much from a space platform, and survey whether the target being watched
contains live green vegetation or not. NDVI stands for „normalized difference vegetation index‟.
The NDVI is calculated as follows:
NDVI = (NIR-VIS) / (NIR+VIS)
Where VIS and NIR stand for the spectral reflectance estimations gained in the visible (red) and
near infrared areas. In vegetation studies, NDVI is used to estimate crop yields, pasture
performance and rangeland carrying capacities among others.
2.5. CRS
Coordinate reference system (CRS) of the map is based on the projection, ellipsoid and datum.
These are measurements which help in modeling the shape of the world. Coordinate reference
system can be divided into two classes. These classes are geo-referenced and non-geo-
referenced. Coordinates are usually geo-referenced unless
There is a special circumstance. In order to find the locations, three types of coordinate reference
systems are used. Firstly, the geographic 3D in which the axes of latitude, longitude and
ellipsoidal height are present. This is commonly used by GPS receivers. Secondly is the
geographic 2D, in which the system has the axes of longitude and latitude. Finally is the
projection of the geo-referenced Cartesian 2D system which contains the axes of northing and
easting. This system is obtained by converting geographic 2D coordinates through the projection
of a map.
2.6. GRASS Plugin:
Geographic Resources Analysis Support System is an open source GIS toolkit and has a large
number of useful raster, vector and terrain tools for GIS analysis. These toolkits can be used with
QGIS using the Grass plug-in.
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3. Tasks
In this task, 12 locations from Kamp-Lintfort have been selected and then I have collected some
background information that place. Then these locations coordinated were recorded using
Google maps.
3.1. Task 1 Task 1 consists of selecting twelve different personal impressions and locations of Kamp-
Lintfort for a local newspaper. I will describe all of the twelve locations one by one. The selected
locations are:
1. Kaufland: A German supermarket chain which also owns Lidl. It is located at Moerser
straße 290, 47475, Kamp-Lintfort.
2. Fatih Market: A shopping place where people can purchase goods. This grocery store is
very popular in Muslims because of the goods. This grocery store is located at Ringstraße
117, 47475, Kamp-Lintfort.
3. Burger King: Place where individuals pay to sit and consume suppers that are cooked and
served in the premises. Its address is Oststraße 26, 47475, Kamp-Lintfort.
4. McDonald’s: Place where individuals pay to sit and consume suppers that are cooked and
served in the premises. Its address is Prinzenstraße 84, 47475, Kamp-Lintfort.
5. Hochschule Rhein-Waal: A high-level educational institution in which students study for
degrees and scholastic examination is carried out. This university is located at Friedrich-
Heinrich-Allee 25, 47475, Kamp-Lintfort.
6. Deutsche-Post Office: The public department or corporation in charge of postal
administrations and information transfers.
7. Neues Rathaus: This is a Public place which is specifically made for the government
purpose. When a new person who didn‟t belong to Germany comes to Kamp-Lintfort he/she
have to register him here in this city.
8. Sparkasse Bank: Sparkasse bank is very popular in Germany now days. This bank is made
in 1999.
9. Student’s Dorm: It is related to Hochschule Rhein-Waal. These dorms are specifically made
for students. These dorms are founded in 2014.
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10. Real: Real is a private corporation related to selling household products. It is situated in
Moerser strasse 221, 47475 Kamp-Lintfort.
11. Sport palest: Sport palest is a private corporation and it is situated in ringstrasse 128, 47475
Kamp-Lintfort.
12. Deutsche Bank: This bank is very popular in students. It is situated in moerser str. 234
47475 Kamp-Lintfort.
Figure 1: Task 1
3.2. Task 2 In this task, 12 locations have been saved as point vector into QGIS. Then the attribute tables
also have been modified in order to add the collected background information about those places.
As point vector consist of 12 places will not be easily recognizable by anyone, Open-Street-Map
data has been added that fits the kamp-linfort area. After this step those places are easily
identifiable as very graphical map has been added as layers. In task 2 (2) we made a table with
different attributes like; North side, East side, Background, Personal Connection & Categories.
North side reveals us information about the north. East side reveals us information about east.
Background reveals us information about the background of that particular attribute. Personal
connection shows us information about the personal connection whether the attribute you
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personally liked or not and why do one like it. In categories, we can categories the specific
attribute like; whet ether it is belong to public building, Private building or something else.
Figure 2: Task 2 (1)
Figure 3: Task 2 (2)
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3.3. Task 3 Travelling salesman problem consists of a salesman and a particular number of cities where a
salesman has to visit each of the cities starting from a particular city and returning back to the
same city while travelling through the other cities. The main goal is to optimize the total
travelling distance. The salesman has to minimize the total length of trip in order to save time
and money. In this task, the twelve places are considered as the total trip of the salesman, and the
shortest path between all the places starting and returning to a particular place has to be
determined.
In this task, Grass plugin has been used to find shortest path between those 12 places.
1. First of all Deutschland map-set has been created.
2. Then, using v.in.ogr.qgis function, 12 points vector & line layer from open-street maps
were imported to grass. Only after this step was apply other functions on this vector
layer.
3. Then, v.net function was used to connect 12 places to line vector layer of openstreet map.
Now we have single vector layer with line (path information) & point (Location of 12
places).
4. After that, the combined layer from previous step was given as input to v.net.salesman
function which created the shortest route between these places.
5. Due complexity in the lines layers taken from openstreet maps, some of the places which
are not connected by v.net.salesman function.
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Figure 4: Task 3
While computing shortest path, „road graph plugin‟ can also be used but it can only be utilized
to find the shortest path between only two places. Therefore, „v.net.salesman‟ tool is used to
compute the shortest path among twelve places.
3.4. Task 4 In this task, The Land set data is imported to the QGIS project and then the Normalized
Difference Vegetation Index (NDVI) of Kamp-Lintfort area is calculated. Satellite images are
collected from the earthexplorer.usgs.gov website. USGS provides satellite images based on
different bands. Then the NDVI is calculated using the raster layer of QGIS using following
formula.
We can apply this formula from Raster-> raster calculator.
NIR: stands for Near Infrared Radiation
VIS: stands for visible radiation
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The Normalized Difference Vegetation Index is digital display application bands of the visible
and near of the electromagnetic spectrum, and adopted analyze measurements and remote
sensing to assess whether the observed target contains green vegetation. [6]
Vegetation appears very different at visible and near-infrared web lengths. In visible light,
vegetated areas are very dark, almost black. And desert regions are light. At near-infrared web
lengths, the vegetation is brighter.
In task 4, green area reveals the vegetation & pink area reveals the other part than vegetation
like; roads, houses, malls, etc.
Figure 5: Task 4
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4. Discussion of results
The project is about creating a map of Kamp-Lintfort presenting 12 places of personal interest. It
consists of various tasks and processes which are conducted step by step. The procedure for
cataloging these twelve places and then integrating them into the QGIS tool is explained in detail
underneath. The geographical points for these sites were integrated into the QGIS project as per
the requirement of task 2. For task 3, the shortest path had to be calculated and for that salesman
tool „v.net.salesman‟ was used to compute the optimal path among the selected places. After
visualizing the results of task 3, this can be declared that the selected regions have the capability
of optimal connectivity among the places. For task 4 the objective was to calculate the NDVI for
the Kamp-Lintfort area. This was done by using raster data and raster data calculator.
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References
[1] M. S. Mesgari and Z. Masoomi, GIS Applications in Public Health as a Decision Making Support
System and It.s Limitation in Iran, World Applied Sciences Journal 3, 73-77, 2008.
[2] Anderson, Mark (18 October 2006). “Global Positioning Tech Inspires Do-It-Yourself Mapping
Project”. National Geographic News. Retrieved 25 February 2012
[3] Qgisworkshop.org, 'QGIS — QGIS Workshop V1.0.0 Documentation'. N.p., 2015. Web. 25 Mar.
2015. Retrieved from: http://www.qgisworkshop.org/html/workshop/qgis.html
[4] Georepository.com, 'Geodetic Parameter Database'. N.p., 2015. Web. 29 Mar. 2015. Retrieved
from: http://georepository.com/home.html
[5] Anderson, Mark (18 October 2006). “Global Positioning Tech Inspires Do-It-Yourself Mapping
Project”. National Geographic News. Retrieved 25 February 2012
[6] Wikipedia 'Normalized Difference Vegetation Index'. N.p., 2015. Web. 25 Mar. 2015. Retrieved
from: http://en.wikipedia.org/wiki/Normalized_Difference_Vegetation_Index