Module 1: Crime Analysis

 Crime analysis in ArcGIS Pro involves using spatial data and geoprocessing tools to identify patterns, trends, and hotspots of criminal activity. By integrating crime incident data with demographic and geographic layers, analysts can perform operations like spatial joins, density mapping, and statistical analysis to better understand where and why crimes are occurring. Tools such as Kernel Density, Local Moran’s I, and attribute-based symbology allow users to visualize high-crime areas and evaluate relationships with social or environmental factors. This type of analysis supports informed decision-making for law enforcement. Below are a few of the maps we completed in the crime analysis lab.



I used a spatial join to calculate homicide counts within a half-mile grid. The top 20% of grid cells with the most homicides were selected and dissolved into a single hotspot polygon. This method is simple and straight forward but may not capture subtler patterns.



The Kernel Density analysis of homicides in Chicago provided a visual representation of where 2017 homicides were most concentrated across the city. By applying a search radius, the analysis generated a smooth raster surface that highlights clusters of high activity without relying on administrative boundaries. This method made it easy to spot general areas of concern, especially in neighborhoods where incidents were tightly grouped. The final map showed continuous zones of high-density homicide activity, offering valuable insights for identifying broad patterns.


Using spatial statistics, I calculated homicide rates by census tract and ran a Local Moran’s analysis. This statistical method identifies significant spatial clusters—in this case, tracts with high homicide rates surrounded by similarly high-rate neighbors. Only the “high-high” clusters were selected and merged into a single polygon. This method offers a data-driven way to find meaningful spatial patterns.

Each mapping technique had its strengths and weaknesses. The Kernel Density map struck the best balance between clarity, accuracy, and practical use for predicting future crimes. It highlighted concentrated hotspots effectively without covering too much area. From a police chief’s perspective,
this method might offer the best guidance for allocating limited resources.
This lab was a great introduction to spatial crime analysis and showed how GIS can be a powerful tool in public safety planning. 

Comments

Post a Comment

Popular posts from this blog

Module 6: Isarithmic Mapping

Image
  In module 6 we focused on Isarithmic mapping. Isarithmic mapping uses lines (isolines) to link points of equal value for continuous data like temperature or rainfall across a map. The pattern and spacing of these lines visually represent the distribution and rate of change of the phenomenon.  The lab for module 6 was quite interesting. We used data from PRISM to complete this lab. PRISM is a group out of Oregon State University that generates detailed maps of monthly and annual climate conditions like precipitation and temperature. It works by combining specific data points with a base grid, such as elevation data or a 30-year climate average. This approach is very effective in mountainous areas because it accounts for how terrain influences weather patterns. Monthly maps are created first, and then annual temperature maps are derived by averaging these monthly values, while annual precipitation maps are calculated by adding the monthly totals. As you can see when viewi...
Read more

Final Project Bobwhite-Manatee Transmission Line

Image
Wow! I do not even know where to begin. This has by far been the most stressful and intensive school project I have ever had to complete. I have worked on this project from 7:00 pm to after 1:00am every weekday this week. Aside from sleep deprivation making this project challenging I also struggled greatly due to the lack of instruction. While I understand that aspect of the assignment these kinds of projects become very challenging for me because I over think the process and end up having a symptom some call "paralysis by analysis." Despite those struggles I pressed through and came out with a halfway decent result. I do wish I had more time on this project to clarify some things and make my data more readable, also due to time constraints there were several things I was no able to compete but for the time being I think my results will be acceptable.  I will give a brief overview of the final project. I only attached two of the maps I created because if I were to add them al...
Read more

Module 4: Data Classification

Image
This lab session was about understanding data classification. The lecture explained different types of data and how they're shown on maps. It then covered various methods for dividing data into categories for visual representation. In the Lab portion, we used census data for Miami-Dade County, Florida, specifically looking at the percentage of the population over 65. We created four different maps of this same information, with each map using a different data classification method. Those classifications were Equal Interval, Quantile, Standard Deviation, and Natural Breaks. We then arranged these four maps on a single layout, including standard map elements. The goal was to visually compare how each classification method displayed the data and what patterns became apparent or less obvious with each approach. Finally, we considered which classification method might be most useful for different purposes, such as identifying areas with a high senior population, and whether using percen...
Read more