Location Decisions

Applications in GIS - Mod 8

This week's assignment was to make a recommendation on places to live for a couple, a doctor who will be working at the North Florida Regional Medical Center, and her husband who will be teaching at the University of Florida, in Alachua County, Florida.

 The criterion set by the couple were nearness to work for both of them, a neighborhood with a high percentages of people 40 to 49 years old, and a neighborhood with high house values.  This map was created with four data frames, one each for each of the criterion.  For the distance frames we ran the proximity analysis tool Euclidean Distance to generate a raster image showing distances out from the points of interest in 3 mile increments.  To allow for easier interpretations and analysis we then reclassified them. Next we added fields to our census tract attribute table to calculate the percentage of people 40-49 and homeowners, then converted these feature classes to rasters and reclassified them so they could be compared to the distance rasters and recommended a few locations for each criteria.

 The next map is where our comparisons were made.  We added our four reclassified layers to the map then created a model with them as the input and the Spatial Analyst Weighted Overlay tool.  For the first data frame we gave each of the criterion equal weight, but for the second we responded to the clients' request to focus more on proximity to workplaces and restricted some of the Scale Values in the distance layers to place them within the least favorable values so they wouldn't be influenced by the weight of the other criteria.  Next the percent of influence was adjusted to give more weight to the distances and less to the population and home ownership.  With this new information we were then able to recommend a few areas evenly spaced between the two locations with the rest of the criteria accounted for.