Week 7 - Location Decision - On Your Own

Military Housing Location

The assignment was to create scenario “On My Own” of selecting a site based on criteria I selected. The topic I chose was potential areas for military housing near the bases located in Okaloosa County Florida.



The first map I created was a base (foundational) map of Okaloosa County. I selected data from the FGDL website and chose Albers Conical Equal Area as my projection. I added data layers for the military owned land, highways, municipalities and water features to complete the map.

Next, I asked the question, what are the factors that are relevant to selecting areas for potential new military housing? The primary needs were, distance from the installation access gates, proximity to sufficient schools, and distance to interstate travel.



A map was created depicting an overlay of distances from the main access gates of the military installations on the county. This map created by using the Spatial Analysis Tools, Euclidian Distance Tool. I created a new point feature file and added the points for the three main access gates of the military installations. I used this feature to overlay distances from, clipping them at the Okaloosa County boundary. I then reclassified the data using 10,000 meter intervals, creating five intervals.

Next I chose to evaluate distances overlaid on the County. I used the Euclidian Distance again, selecting the layer for I-10 as my feature with the County as the clipping feature. Once again I reclassified the data to create a scale of 1-9 for the interval.

The next map was a little tricky. I wanted to determine if a municipality had the schools sufficient to house kids associated with the new troops. For this I used two layers, the first one from the National Atlas for the United States for the community data and one from the Department of Education and clipped it to the county boundary. Next I summarized the data from the DOE by city name, selecting student population as a criterion. Then I joined the summary table to the Atlas data to give me a school population by community number. From this I used the Point Density Tool to give me a raster of the population. Once again I reclassified to nine different classes, with class 1 being 0-99 and up.

The last step of my analysis was the creation of the results. Map 1 is a depiction of creating a tool for performing a weighted overlay using an equal weighting factor for each of the criteria.

Map 2 was created by the same method only giving equal weight to distance from I-10 and bases with a greater weight to the schools.

The pros and cons. The pro of this method is that two areas that clearly meet the test are the Niceville and Crestview areas. They have substantial school capacity as well as being the closest in proximity to the base. Crestview rates high due to its location adjacent to I-10. The con to this method however is that available properly zoned properties were not factored into the decision. Neither was the capacity for the roadways to carry additional vehicular traffic without significant upgrades.