Module 6 - Suitability Analysis

    This week, in the sixth Applications in GIS lab, was about Suitability Analysis.

    In this lab we utilized more of our skills with ArcGIS to do sustainability analysis on a study area in Oregon. In the first part of the lab it was us attempting to do analysis to find where there would be possible mountain lion habitats within the study area. Although it will not be presented within this blog, the analysis proved a good warmup for the map we will be presenting.

    In the map below, you will see a suitability analysis of the study area with concerns to property development. This analysis first started with reclassifying land cover with ratings from 1 to 5. The desirable areas are labeled 5, like agriculture and meadows, while the lower end is 1 with urban and rivers. Following this, we did the same to soils after changing it from a polygon to a raster. For Soils we also rated it 1 to 5. Moving on, we also did the same for elevation after changing it to degrees so we could change its value more easier. With this layer, we wanted areas where it less inclined or flat, so we made a reclass range of increasing values from 0-2, 2-5, 5-8, 8-12, and >12. We also gave these values a range of 1 to 5. Next with the river layer we gave it some Euclidian distance in order for us to be able to reclass distance within 1000 feet as 1 and distance beyond 1000 feet as 5. We did the same thing for roads, except 1320 feet away and adding it again for how far it is with decreasing value. 

    Once all of that was done, we combined our layers with weighted analysis and got the maps you see below. The map on the left is the study area with an equal percentage, whereas the alternative percentages are different and displayed on the map.


    In it we can see the green (5) areas are the more suitable areas for development than the redder values. Personally I think this analysis was another great use of applying the use of ArcGIS to a real world scenario, and I can't wait to see what it will be used with next. 

 

Comments

Popular posts from this blog

About me

Module 4 - Data Classification

Module 1 - Fundamentals