GIS5100 Module 1: Crime Analysis
Getting the ball rolling again after a nice vacation has been hard, but I'm doing my best to stay on top of things, especially with a few extra days off thanks to the July 4th weekend. To dive right into the swing of things, it's the next course on Applications in GIS, featuring the first Module on Crime Analysis. The work I do doesn't f ocus on identifying and analyzing hotspots, so it was a nice change of pace to learn and work through the process of creating different types of hotspot maps and how such data can assist in crime prediction. The three main types of hotspot analyses that were covered were Grid Overlay, Kernel Density, and Local Moran's I. The two main datasets we worked with were in Washington, DC and Chicago, Illinois. Washington, DC's data helped us get a foundation for learning how to prepare burglary rates in a choropleth map. Then, we created kernel density hotspots in DC as well. From there, we went to Chicago and created 3 hotspot maps: Grid, ...