GIS5100: Module 1 - Crime Analysis

 

For this lab, I analyzed the spatial distribution of homicides in Chicago for the year 2017 using three different techniques. Grid-based mapping, Kernel Density Estimation, and Local Moran's 1. The ultimate goal was to determine the patterns of crime in the location and evaluate which method would best predict the locations of homicides in 2018. 

The maps are in order as follows. Map 1 - Grid-based mapping. Map 2 - Kernel Density Estimation. Map 3 - Local Morans 1. Each method highlighted crime concentrations but differed in a few ways. The grid-based mapping was the simplest and relied heavily on the position of the grids. The kernel density provided good patterns but covered large areas and was generalized. The best, in my opinion, was Local Morans 1. This technique used real-world boundaries to identify clusters and where they intersected. 

I think this lab was very useful for understanding how maps can be used and for understanding different ways of displaying information. The hotspot analysis showed that using GIS techniques can have real-world applications, reducing crime and improving policing by showing crime hotspots.