GIS 4048: Week 8 - Urban Planning: Location Decisions

Unfortunately, we we finished up the crime analysis section, but now we get to take a look at urban planning and location decisions. This week's assignment focused on finding a home for a couple within Alachua County, Florida.  She has accepted a position at North Florida Regional Medical Center (NFRMC) and he plans to teach at the University of Florida.  They want to live somewhere that's close to both NFRMC and UF, as well as within a neighborhood with a high percentage of people aged 40-49 years old, and in a neighborhood with high house values.  

The map above displays Alachua County, Florida with all of the public lands within the county.  This map was compiled in ArcMap then all of the layers were placed into a basemap layer. Once placed into a basemap layer, ArcMap will draw the layer using optimized map display logic. 

This map is a compilation of four data frames. The two on the left were created using the Euclidean Distance tool centered on NFRMC (top) and UF (bottom). This criteria is important to a couple who are looking to buy a house located near NFRMC and UF.  The two data frames displayed on the right are showing U.S. Census Bureau Census Tracts by the percentage of people aged 40-49, and the percentage of homeowners.  This criteria is important for those looking to buy a home within a neighborhood that has a high percentage of that particular age range, and in a neighborhood with high house values. 

Using the data from the previous map, I was able to create two weighted overlays to help the couple determine where they should start looking to buy their new home.  Upon landing jobs in the county, it became more important for them to be closer to NFRMC and UF.  For the overlay shown on the left, I set the equal influence so each criterion is weighed the same.  As for the overlay on the right, I increased the influence on the distance criteria for each to produce the second overlay.