For my final project I had to conduct different analyses to find suitable locations for a family and their new home. Mrs. Jones has just accepted a new job at Nova Southeastern University in Broward County. Her, her husband, and their child wish to hire a GIS Analyst to find the best location for their new home. Because of her new job, she wishes to live in close proximity to NSU. And because of her child, she also wishes to be close to specific daycares and West Broward Pediatrics. Other criteria include a higher percentage of family households, homeowners, and neighbors aged 30 to 39.
For this assignment, I planned to use the Euclidean Distance tool and the Reclassify tool on the proximity criteria. For the other criteria, I planned to use the Feature to Raster tool and then also Reclassify that.
For the proximity criteria, I simply isolated the specific locations and created their own layers. After, I used the Euclidean Distance tool and Reclassified that output raster. Reclassifying enables the data to be better interpreted and makes it easier to compare to other maps.
For the population criteria, I added a new field to each attribute table and used the field calculator to add the percentages. After, I converted these values to a raster file and reclassified that for easier viewing. Below is the map I created using these tools.
I also created two weighted overlay maps. I created a model from the ModelBuilder to make this process easier. The input files were the 6 reclassified raster files from the previous step, and the first map had equal influence for all the criteria. The second map used the same model but each criteria was weighed differently, based on the clients preference. Below is the map I created from using this model.
I thought this project was a lot of fun. I thought my results turned out okay. Maybe if I were to do this project again, I would create more interesting criteria or maybe used different tools. I’m also curious how the final results would turn out if I had changed the weighted influences. Would I have gotten better, more interestinf results? It’s a fun thought to experiment with.