Tutorial II: Data Management
This training introduces several useful pieces of analytical GIS functionality with health applications including: geocoding, spatial joins, and essential geoprocessing tasks like clip, buffer, and project. Each module includes a lecture, a hands-on exercise using ArcGIS, and the data needed to complete the exercise. You must have access to ArcGIS Pro in order to complete this training series.
This training is part of a larger curriculum created as part of the GIS Surveillance for Heart Disease, Stroke, and Other Chronic Diseases in State and Local Health Departments project.
Learn more about the other GIS Training programs.
Module 2.1 Generating and Managing Spatial Data
Goals: The goals of this exercise are to use batch geocoding to update locations of farmers markets in Rhode Island and visualize a 1-mile distance from the farmers markets.
Skills: After completing this exercise, you will be able to use both the batch geocoder tool and the interactive matching tool to geocode a table of addresses in ArcGIS Pro. You will also know how to use common geoprocessing tools such as Merge and Buffer.
Module 2.2 Leveraging the What and Where of Spatial Data
Goals: The goals for this exercise are to gain experience performing table operations: attribute selections and calculating new fields; and spatial joins.
Skills: After completing this exercise, you will be able to:
- Confidently perform attribute selections, add new fields to tables and calculate values for fields; and
- Spatially join a point dataset (businesses of interest) to a polygon dataset (census tracts). This is a useful method for the enumeration of
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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.
