Difference between revisions of "Exploring Hydrological Analyses using ILWIS"

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===Creating Coordinate System===
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===Creating a Coordinate System===
 
The DEM for this exercise is in a geographic coordinate system and for an easier hydrological analysis, it should be converted into a projected coordinate system.
 
The DEM for this exercise is in a geographic coordinate system and for an easier hydrological analysis, it should be converted into a projected coordinate system.
   

Revision as of 21:44, 18 December 2014

Purpose

This Wiki tutorial has been produced for the purpose of exploring and describing the methods used for hydrological analyses in ILWIS (a FOSS4G program). The objective of this tutorial is to provide users with a better understanding of how the hydrological analyses within ILWIS works, in addition to providing the instructions necessary to reach the desired output for their study region. Additionally, this tutorial will allow for comparison of ILWIS and SAGA GIS, using the same data for analysis as the Exploring Hydrological Analyses using SAGA GIS tutorial from 2013.

Introduction to ILWIS and the Project Tutorial

ILWIS stands for "Integrated Land and Water Information System". It is a open source Geographic Information System software program that was designed to be a user-friendly integrated software that contains both raster and vector processing capabilities, allowing for both analyses on remotely sensed images, vector maps and numerous spatial modeling abilities. ILWIS was developed by the International Institute for Aerospace Survey and Earth Sciences (ITC) in The Netherlands. This tutorial will focus on its ability to use Digital Elevation Models (DEMs)to run hydrological analyses of a study region. More information about this product can be found on the ILWIS Website

Ilwis logo.png

This project will focus on hydrological analysis of Okanagan Lake, a popular tourist destination in British Columbia, Canada. The tutorial will cover topics such as Aspect mapping, Slope mapping, Watershed Delineation mapping and Wetness Index mapping through the use of ILWIS hydrological analysis tools.

Methods

Data

In order to carry out this exercise, a DEM of the area of interest is needed. For this project a open source DEM was obtained using the Geospatial Data Extractiontool created by Natural Resources Canada.

For DEMs located outside of Canada open source DEMs can be obtained from ASTER and SRTM Global Digital Elevation Model - USGS

Getting Started

Before starting any analysis, create your working folder and ensure all data needed for the exercise are in this folder. Keeping all your data in one folder will make analysis easier.

Starting ILWIS

ILWIS 3.08.03 can be downloaded for free from 52 North.The newer version of ILWIS 3.08.04 is available but do not download this one, as a bug does not allow you to import DEMs into this version.

  • Ensure that ILWIS 3.08.03 is properly installed on your computer
  • Locate ILWIS from the Program list and double click on the icon to launch program.
  • ILWIS main page will open
  • Use the ILWIS Navigator Tab to locate your working folder. The Navigator lists all drivers and directories.

INSERT main page picture here

Figure ??: Screenshot of ILWIS Interface

Importing DEMs

1) Click Operations --> Import/Export --> GDAL (Geospatial Data Abstraction Library)

printscreen

2) An Import window will open

3) Click to the DEM you want to import and ensure that the import format is Use GDAL.

5) Give your Output DEM a name and click OK

6) To view your DEM go to Operations -> Visualization -> Show map. A new window will open with the DEM.


Creating a Coordinate System

The DEM for this exercise is in a geographic coordinate system and for an easier hydrological analysis, it should be converted into a projected coordinate system.

To assign coordinate system use the following steps:

1) Go to ILWIS main interface

2) Click File and scroll to Create and choose Coordinate System

Coord1.png

3) Give Name, select CoordSystem Projection and click OK

Coord2.png

4) Select the suitable Projection and click OK

Coord3.png

5) Click the Ellipsoid tab, select the appropriate Ellipsoid and click OK

Coord4.png

6) Click on Datum tab, select the appropriate Datum and click OK

Coord5.png

7) Enter the suitable Zone (if necessary)

Coord6.png


Assigning Coordinate to Vector datasets

1) Right click on the vector data and choose properties

Coord vector1.png

2) Change the Coordinate system to the one created earlier (Zone18)

Coord vector2.png

3) Click Apply and OK

Coord vector3.png

4) Repeat steps 1-3 for all the vector datasets

Vector to Raster

Since the Spatial Multiple Criteria Evaluation analysis will be done using raster data; hence there is need to convert all input data to raster. For vector to raster data conversion, follow the steps below:

1) Click with the right mouse button on the vector map and select ‘Polygon to Raster’ from the menu

V Raster1.png

2) Click on the button beside GeoReference Tab

V Raster2.bmp

3) Give a GeoReference Name (Ottawa_n)

4) Click the Coordinate System drop down and choose coordinate system (Zone 18) created earlier

V Raster3.png

5) Click show to open the raster data

6) To ensure the all input data have the same GeoReference, use the GeoReference (Ottawa_n) created in steps 2-4 when converting other vector data to raster.

V Raster4.png

Creating Buffer

Parts of the criteria set for sitting the landfill are proximities to major roads and water-bodies; therefore buffers are to be created around major roads and water-bodies. To create buffer in ILWIS, follow the steps below:

1) Right click on the raster data and scroll to Raster Operations, then choose Distance Calculation

Buffer1.png

2) Give name to Output Raster Map

3) Choose distance as Domain

4) Specify distance and click show to view the map

5) Repeat the steps 1-4 for other data to be buffered.

Buffer2.bmp

Figures below are the results of the buffer generated:

Buffer3.png

Figure 9: Screenshot showing Road Buffer


Buffer4.png

Figure 10: Screenshot showing Waterbody Buffer

Contour to DEM

1) Right click on the contour data, Scroll to Segment Operations, then Attribute Map

Cont1.png

2) Change Attribute to the field that contain the Z values, then give name to Output Segment Map

Cont2.png

3) Click show to view the map

4) Right click on the newly created contour data (Contour_Zvalue) and scroll to Contour Interpolation

Cont3.png

5) Give Output name (DEM), choose the GeoReference created earlier, leave Domain as value

Cont4.png

6) Click show to view the map

New DEM.png

Figure 11: Screenshot showing DEM

DEM to Slope

Creating DFDX and DFDY

1) Right click on DEM data, choose Image Processing>Filter

Slope1.png

2) Choose Linear as Filter Type and Filter name to DFDX

3) Give Output name and click show to view the map

Slope2.png

4) Repeat the same process to create DFDY

Slope3.png

Creating Slope

1) From the Finder Table of Content, double click Map Calculation

Slope4.png

2) Type this formula: 100*HYP (DX, DY)/PIXSIZE (DEM) into the Expression Space

Note: Change DX, DY and DEM using your own data

3) Give Output name and choose value as Domain

4) Click Show to view the map

Slope5.png

Slope6.png

Figure 12: Screenshot showing Derived Slope

Creating Domain for Slope Classification

1) Click File, then Create and click on Domain

Slope7.png

2) Give Domain Name, Check Class and Group

3) Click Ok to Continue

Slope8.png

4) Click on add Item to add all classes

Slope9.png

Slope10.png

Slope11.png

Combining Slope with Domain

1) Right click on the Slope data, Go to Image Processing and Click on Slicing

Slope12.png

2) Give Output Name and Choose Domain created earlier as Domain (Slope_class)

Slope13.png

3) Click Show to view the Slope Classification Map

Slope14.png

Figure 13: Screenshot showing Slope Classification

Spatial Multi-Criteria Evaluation Analysis

Getting Started with SMCE

1) From the Operation Tree, double click on Spatial Multi-Criteria Evaluation


SMCE1n.bmp

2) Both the Problem Analysis and Decision Making modules will be used to find the suitable Landfill sites

3) Select on Problem Analysis and click OK to open the SMCE workspace

SMCE2.bmp

SMCE3.png

4) Click File>Save to save the SMCE project

5) Double click on New Goal to rename it and click on ‘filename given’ to give output name

SMCE4.png

Adding factors and constraints data

1) Click on insert Spatial Factor icon or click Edit>Insert>Spatial Factor to inset all 'Factors' data

Factor1.png

Factor2.png

2) Click on Insert Spatial Constraint icon or click Edit>Insert>Spatial Constraint to insert all 'Constraints' data

Factor3.bmp

Factor4.png

Standardize factors and constraints

1) To standardize factors, change to Multi Criteria Analysis Mode

Standard1.png

2) Right click on the factor data and choose standardize

Standard2.png

3) To create standard for slope, enter the minimum and maximum suitable slope values

Standard3.png


4) To standardize the road data, right click on the road raster data and choose standardize.

5) Here, I chose Cost and Goal as Method and entered range scores

Standard4.png

6) Repeat the same steps to standardize waterbody

Standard5.png

Assigning weight (Pairwise)

1) To assign weight, right click on the goal name (Landfill) under ‘Criteria Tree’ and choose Weigh or click on Weigh icon.

Weight1.bmp

2) I chose the Interactive ‘Pairwise Method’ and clicked Ok to continue

Below are the weights assigned to each factor:

3) Here, I clicked the drop down box and I chose ‘Road is moderately less important than Lake

Weight2.png

4) Repeat the same for Road, Slope and Lake, Slope

Weight3.png

Weight4.png

Note: There are other two methods of assigning weights which also be used

Pairwise Comparison Results


Weight5.png

Running Spatial Multi Criteria Evaluation Module

1) To run the SMCE module to create the suitability map for Landfill, click on Generate and choose ‘All Output’

SMCE 1.png

2) Wait a while for the analysis to finish and click Ok to view the map

Landfill1.bmp

Figure 14: Screenshot showing Suitable Landfill Sites

Interpretation of Result

SMCE map shows values ranging from 0-1; a value of 0 denoted with colour Red indicates less suitable areas. The more the values move towards 1, the more acceptable such areas are, i.e. transitions from Yellow to lemon and finally Green indicates the most suitable sites.

Conclusion

This tutorial showed the steps required for suitability mapping for landfill in the City of Ottawa, using the analytical functions of SMCE module in ILWIS software. Decision Tree wizard was used to add factors and constraints; to standardize and assign weights to the constraints and factors for successful execution of the decision processes. Finally, SMCE analysis was carried out to derive the suitability map for the landfill.

References

  • Agus (2011), Modeling Spatial Analysis for Identifying Landslides Areas in Sumedang

http://www.scribd.com/doc/76923076/Analysis-spatial-using-ILWIS

  • Mohammed A. Sharifi and Vasilios Retsios,(2004), Site selection for waste disposal through spatial multiple criteria decision analysis

http://www.itl.waw.pl/czasopisma/JTIT/2004/3/28.pdf

  • Multi Hazard Risk Assessment

http://www.ecapra.org/sites/default/files/documents/Book%20Multi%20Hazard%20Risk%20Assessment_0.pdf

  • 52 North

http://52north.org/communities/ilwis