Congratulations to David Schroeder on being named GIS Online Student Spotlight for his outstanding work in Applications in GIS (GIS 4048).
David hails from Temecula, CA, where he works in the public finance field working closely with municipalities and other government entities. He is a busy family guy with a wife, two kids, and two dogs. When not producing high-quality GIS deliverables, you can find David watching sports, spending time outdoors, or searching for the best stout beer in town. Welcome to the spotlight David! Have a beer to celebrate! To follow David's work throughout the program, check out his blog at David Schroeder - GIS Blog.
Module 5: Crime AnalysisInstructor: Penelope Mitchell
The Washington D.C. Crime Analysis lab kicked off the Homeland Security and Law Enforcement topic. Students utilized crime data from the DC Metropolitan Police Department to determine crime patterns in proximity to police stations and to identify underserved area(s) potentially in need of a police substation to curb crime. Additionally students utilized density analysis to locate hot spots of certain crimes.
Student Learning Outcomes:
- Establish workspace environments
- Analyze data stored in a Microsoft Excel Database
- Create data using the Display XY tool
- Create an address locator using street data
- Geocode tabular address data to point features
- Explore the Marker Symbol Options
- Prepare data for processing in a geodatabase including, but not limited to, proper nomenclature
- Use Field Calculator to calculate attribute table values
- Perform multiple ring buffers and create spatial joins in the attribute tables
- Utilize Swipe Tool to allow crime cluster distributions to be displayed over census block data
- Create Multiple data frame maps to show various crime distributions
- Use Kernel Density to display crime clusters
- Compile and present results for real world problem solving
David’s crime analysis map stood out as a spotlight for it’s crisp and clear presentation and the ease to which it communicates results. The range graded police symbols are classified and symbolized for quick data acquisition--it is clear at a glance which police stations handle the most crime. The added subtext on the map provides useful information such as an overview of DC crime patterns, the location of the proposed substation and why. The crime graphs easily and aesthetically communicate the crime dynamics of city. Excellent work David!
Next week, we will spotlight a student from GIS 5100 - Application in GIS taught by Dr. Paul Zandbergen.