Spatial analysis

To get the suitable area to open a new liquor store, I am using the Multi-Criteria Evaluation with non-Boolean standardization and Weighted Linear Combination. Before I can do the MCE, I have to do some other analysis to prepare a set of images for it.

I RECLASS all the images which has categorize the data into ranges. Then, I use FRICTION to create some friction-cost images. Afterward, I use COST DISTANCES to caculate the cost surfaces of all the factor images with the store location image.

To do the MCE analysis, I need to convert all the images into bytes (0-255) by using FUZZY. Then I use WEIGHT to create a pairwise matrix comparison for the MCE. Combining with my contraint images with the pairwise comparison file, the analysis result will be produced.

My idea here is to assumed there is a cost for every different factor, and try to find the least cost area where a new liquor store should be place. However, I use it in another way. Trying to put it as a grading system. The higher grade (value) the area has, the more suitable it is.

Area satisfying criteria:

Income

catographic model

Image1 - INCOME_RECLASS