Results
The two maps below have been reclassed into unsuitable, lowest suitability, low suitability, medium suitability, high suitability, and highest suitability. The reason for this was to create a map that better illustrated the areas that were of the highest suitability for locating a new coffee shop in Vancouver. The scale of suitability from 0 to 255 was reclassed to:
0 0 0
1 1 1
2 100 150
3 150 185
4 185 215
5 215 99999
The reason for this was that I felt breaking up the data at these points best represented the results.
The user defined MCE map shows that the areas of highest suitability are located in downtown Vancouver. The map has more medium, high and highest suuitability downtown because in downtown Vancouver there is a high population of people aged 25-60 years old, there are 4 skytrain stations, and a large number of major roads. This means that the due to the fact that they are given a greater importance then any of the other factors, they are the dominant factors and so any location with the 3 of them would be an area high suitability. Furthermore, downtown is also an area where lots of people take public transit to work and has a high percent of people making over 20,000 dollars after tax. All of these factors are the reason that in the user-defined final map downtown has the highest suitability.
The equal weights map shows similar results however, because all factors are equally weighted in this map their are less areas where all the criteria is met to create the highest suitability. Because they all have the same weights no one factor can compensat for another and still give the map a high suitability.
The difference between the user-defined map and equal weights map illustrates how to maps generated from the same data can produce different results based solely on how you weight the different factors in your multi-criteria evaluation.