Matriculation number:

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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

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 Material from the published or unpublished work of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