Tutorial IV: Special Topics
Module 4.1 ArcGIS Online
Goals: The goal for this exercise is to publish your research output as an online map for the general public.
Skills: After completing this exercise, you will be able to publish your local data to the web. You will also be able to use multiple interactive maps to tell a story to your target audience.
Estimated time to complete: 40 minutes
- Module 4.1 Cdc-pdf[PDF – 996 KB]
- Module 4.1 Exercise Cdc-pdf[PDF – 1 MB]
- Module 4.1 Data Cdc-zip[ZIP – 9 MB]
Module 4.2 Generating Composite Measures
Goals: The goal of this exercise is to generate an ACS based areal measure to understand the social makeup of a defined study area.
Skills: After completing this exercise you will have experience processing readily available US Census (tract level boundary files) and American Community Survey (Social-demographic-economic tables) to generate a composite measure that can begin to provide insight on some of the social drivers that may influence health outcomes for sub county areas of interest.
Estimated time to complete: 30 minutes
- Module 4.2 Cdc-pdf[PDF – 798 KB]
- Module 4.2 Exercise Cdc-pdf[PDF – 403 KB]
- Module 4.2 Data Cdc-zip[ZIP – 9 MB]
Module 4.3 Mapping Uncertainty
Goals: The goal for this exercise is to explore techniques to map and evaluate uncertainty in data estimates.
Skills: After completing this exercise, you will be able to map error measurements using overlay techniques, and check for significant differences among values and classes. And evaluate the statistically significant value difference over time.
Estimated time to complete: 45 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.