Tutorial III: Analysis
Module 3.1: Network Analyst
Goals: The goal of this exercise is to learn how to use the Network Analyst tools to perform network-based analyses. Specifically, you will learn to use the Network Analyst Extension to add network locations, set your analysis properties, and perform a basic service area analysis.
Skills: After completing this exercise, you should have a basic familiarity with Network Analyst Tools and have experience performing a service area analysis.
Estimated time to complete: 50 minutes
- Module 1 Cdc-pdf[PDF – 1 MB]
- Module 1 Exercise Cdc-pdf[PDF – 708 KB]
- Module 1 Shapefile Data Cdc-zip[ZIP – 3 MB]
- Module 1 Street Locator Data Cdc-zip[ZIP – 1.8 GB]
Module 3.2: Spatial Analyst
This module discusses the Spatial Analyst toolset, specifically the interpolation and zonal tools, to perform GIS analyses. After completing the exercise, you should be familiar with raster based analyses and the Spatial Analyst toolset.
- Module 2 Cdc-pdf[PDF-546K]
- Module 2 Exercise Cdc-pdf[PDF-411K]
- Module 2 Exercise Data Cdc-zip[ZIP-3.0M]
Module 3.3: Proximity Analysis
Part 1 Goals: The goal of this exercise is to compare the results proximity based analyses that evaluate geographic access to Federally Qualified Health Care Centers (FQHC) in the Twin Cities Area of MN. First you will calculate a half mile Euclidean distance from each FQHC using the buffer tool, next you will calculate half mile Network based distance service area for each FQHC. With this measures you will estimate geographic access to each US Census Tract level population aggregated to the geometric centroid AND its population weighted centroid.
Part 1 Skills: After completing this exercise, you should have a basic familiarity with both Euclidean and Network based proximity analyses and have an understanding of the implications of population aggregation.
Estimated time to complete: 1 hour
- Module 3 Cdc-pdf[PDF – 956 KB]
- Module 3, part 1 Exercise Cdc-pdf[PDF – 931 KB]
- Module 3 Exercise Data Cdc-zip[ZIP – 3 MB]
Part 2 Goals: The goal of this exercise is to compare the results proximity based analyses seeing to get an understanding of evaluate geographic access at a statewide scale to a select set of resources: Pharmacies and Pharmacist within the state of MN. First you will calculate the Euclidean distance using the generate near table tool, next you will calculate Network based estimates using an Origin Destination (OD) cost matrix. With this measures you will estimate geographic access for each US Census Tract population aggregated its population weighted centroid.
Part 2 Skills: After completing this exercise, you should have a basic familiarity with both Euclidean and Network based proximity analyses and have an understanding of the implications of population aggregation.
Estimated time to complete: 45 minutes
Module 3.4: Analyzing Patterns
Goals: The goal of this exercise is to explore how to analyze patterns in your data. You will first create population weighted centroids (PwC) for census tracts in California to conceptualize where your population lives; and you are going to use recently generated population centers to inform the hotspot analysis on high blood pressure prevalence in the Greater Los Angeles Area.
Skills: After completing this exercise, you will be able to generate population weighted centroids at different scales. You will learn how to use hotspot analysis tool provided by ArcGIS, and properly interpret the hotspot map.
Estimated time to complete: 20 minutes
This GIS training curriculum was developed by the Children’s Environmental Health Initiative in partnership with the U.S. Centers for Disease Control and Prevention, Division for Heart Disease and Stroke Prevention.
The Children’s Environmental Health Initiative (CEHI) is a research, education, and outreach program committed to fostering environments where all people can prosper. CEHI has developed, maintains, and extends an extensive fully spatially referenced data architecture on children’s environmental health. This makes it possible to jointly consider diverse variables collected by different disciplines, creating the opportunity to explore the complex and dynamic relationships among the components of health.