The above is a comparison of two methods of suitability analysis, both performed on raster data, and both created using a weighted overlay process. The weighted overlay model assigns a weighted relative value to each raster cell, the difference between the two maps above being the equal weights scenario assigns the same level of importance to each of the five input values, and the alternative scenario assigns a different percent weight to each. Each cell's value in the final output is a result of combining the relative values of the five inputs, which were raster data indicating certain criteria- such as land cover, slope, distance from rivers and roads and type of soil. The values of the input cells for each criteria were based on a 1 - 5 scale, with higher values representing locations more desirable, such as those nearer to rivers and with certain types of soil. By combining the five weighted values for the input (criteria) rasters, an output composed of cells indicating the relative suitability of an area, based upon the desired criteria, can be produced for a location like the study area in the maps above.
In which I created maps as an official GIS student, with the aim of once again becoming an official GIS professional. Having now achieved said aim, at this time the blog serves as a visual record of my graduate academic pursuits.
Sunday, May 24, 2015
Land Use Suitability Modeling
If you've ever taken the time to consider, for some location, why something is there, whether it be man-mad or naturally occurring, you may be able to understand why land use suitability analyses and models are done. The particulars of how these are typically structured and carried out is our topic for this week.
The above is a comparison of two methods of suitability analysis, both performed on raster data, and both created using a weighted overlay process. The weighted overlay model assigns a weighted relative value to each raster cell, the difference between the two maps above being the equal weights scenario assigns the same level of importance to each of the five input values, and the alternative scenario assigns a different percent weight to each. Each cell's value in the final output is a result of combining the relative values of the five inputs, which were raster data indicating certain criteria- such as land cover, slope, distance from rivers and roads and type of soil. The values of the input cells for each criteria were based on a 1 - 5 scale, with higher values representing locations more desirable, such as those nearer to rivers and with certain types of soil. By combining the five weighted values for the input (criteria) rasters, an output composed of cells indicating the relative suitability of an area, based upon the desired criteria, can be produced for a location like the study area in the maps above.
The above is a comparison of two methods of suitability analysis, both performed on raster data, and both created using a weighted overlay process. The weighted overlay model assigns a weighted relative value to each raster cell, the difference between the two maps above being the equal weights scenario assigns the same level of importance to each of the five input values, and the alternative scenario assigns a different percent weight to each. Each cell's value in the final output is a result of combining the relative values of the five inputs, which were raster data indicating certain criteria- such as land cover, slope, distance from rivers and roads and type of soil. The values of the input cells for each criteria were based on a 1 - 5 scale, with higher values representing locations more desirable, such as those nearer to rivers and with certain types of soil. By combining the five weighted values for the input (criteria) rasters, an output composed of cells indicating the relative suitability of an area, based upon the desired criteria, can be produced for a location like the study area in the maps above.
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