For our final project, we were asked to create a location decision criteria map for clients looking to buy a home within a certain area. My clients are looking to buy a home in Orange County, Florida within the next couple of months. Mr. Cahill retired as a corporal for the United States Marine Corps and initially planned on staying home to watch over their two kids - a 7-year-old daughter and an 8-month-old son. However, he may seek employment options once the family settled into their new place. Mrs. Cahill got a job as a crime analyst for the Orange County Sheriff's Office (OCSO), which is the sole reason behind their move. The clients provided a list of priorities in order for them to find the perfect place for their new home. It's a requirement for them to live in close proximity to the OCSO, as well as an elementary school for their daughter. It's also important for them to live in an area with low crime rates. They also request to be near a day care facility, and live in an area with people who are 22-39 years old, and in an area with a high percentage of homeowners.
In finding the perfect place for them to live, I conducted multiple analyses. First, the Euclidean Distance tool was used to determine the distances from the OCSO, local elementary schools, and local day care facilities. I then created a population analysis, which shows the percentage of people who are 22-39 years old, as well as the percentage of homeowners. Then, I created a crime map to show the variety of crimes that occur within the Orlando area. With this information, I was able to create a Kernel Density map showing the density of three chosen crimes - burglaries, aggravated assaults, and homicides. These crimes were chosen because they appear the most violent. I then reclassified any required data in order to perform a Weighted Overlay Analysis. This analysis shows the best possible locations for the clients, based on equal and set weights. All of the factors were weighted equally during the first overlay. When creating the second overlay, the factors were set to specific weights, based on the priorities of the clients. Using this, I was then able to choose three recommended suitable locations in the area.
Overall, I'm very pleased with the results of all the maps I created. I learned a lot throughout this past semester and I really enjoyed putting all of my newly retained knowledge to work. Looking back on this project, if I could do something differently, I would probably start with an easier state, rather than trying to work with Hawaii - which was my original plan. Hawaii was extremely tough to work with because I couldn't find any of the data I needed and that ended up setting me back 2-3 days. If I had to create another deliverable to submit, I would add "In close proximity to nearby tourist attractions" to the list of criterion and create a map showing those tourist attractions. I would also use that information to create a Euclidean Distance Analysis, as well as a Weighted Overlay Analysis.
Final PowerPoint Presentation
