Crime Analysis

This week's task was to examine homicide rates in Chicago in 2017. I created three types of maps: grid-based thematic, kernel density, and Local Moran's I. To create the grid-based thematic map, I first created a spatial join between the grid raster and the 2017 homicide points. Next, I used the Select By Attributes tool to select all of the cells that contained a homicide. Then I selected the top quintile grids and created a new shapefile, which I used the Dissolve tool to convert the feature class into a single polygon.

   

To create the kernel density map, I used the Kernel Density tool with the homicide points as the input point feature. I edited the symbology to include only two break values. Then I used the Reclassify tool to adjust the two breaks to coded 1 and 2. Next, I used the Raster to Polygon tool to convert the raster. Finally, I used the Select by Attribute tool to select only the values that were three times above the mean.

To create the Local Moran’s I map, I first created a spatial join between the census tract and the 2017 homicide tables. I chose to join using the common area field. I then used the field calculator to determine the number of homicides per 1000 housing units. I used the Cluster and Outlier Analysis (Anselin Local Moran’s I) tool to create the local Moran’s I data. Next, I used the Select By Attribute tool to select and display the high-high clusters. Finally, I used the Dissolve tool to convert the raster into a single polygon.