GeoEnrichment is the process of enhancing your spatial data by appending demographic variables to polygons, describing the people and places within those areas.
You can perform GeoEnrichment-related operations in ArcGIS GeoAnalytics Engine using the GeoEnrich and GeoEnrichVariables tools. These tools allow you to select and append variables from Esri-provided GeoEnrichment datasets to your input polygons.
GeoEnrichment with GeoAnalytics Engine requires the geoanalytics-geoenrichment jar.
See the Install and set up documentation for more information on how to install
this jar to your environment.
GeoEnrichment Datasets
GeoEnrichment tools do not generate demographic variables on their own. They require a compatible GeoEnrichment dataset that packages demographic variables, source metadata, and supporting data needed to append variables to your input polygons.
Starting with version 2.1.0, GeoAnalytics Engine includes a GeoEnrichment Essentials dataset. The dataset provides a focused set of variables for common GeoEnrichment workflows. The dataset contains 431 variables, including core demographic variables from ACS and U.S. Census datasets, along with supporting MOE and REL fields used for validation. For GeoEnrichment data setup instructions, see GeoEnrichment dataset setup.
When you inspect variables with GeoEnrichVariables, some variables are intended for direct use in GeoEnrichment analysis, while others are supporting fields that help you validate or interpret those results. A simple way to tell them apart is to look at the variable prefix:
- Variables that begin with the
ACSprefix are the primary values to use in ACS-based analysis. For example,ACSis the ACS estimate for households (HHr) headed by 15-to-24-year-olds with an annual income below $10,000 from the American Community Survey (ACS) 5-Year Estimates.A15 I0 - The shared suffix identifies the same underlying measure across related fields. In the example above,
A15links the estimate (I0 ACS) with its validation fields (A15 I0 MOEandA15 I0 REL).A15 I0 - Variables that begin with
MOEare Margin of Error fields for the matching ACS estimate. For example,MOEcontains the uncertainty measure forA15 I0 ACSand is useful for validation, not as the main analysis value.A15 I0 - Variables that begin with
RELare reliability fields for the matching ACS estimate. For example,RELindicates how reliableA15 I0 ACSis and should be used to assess fitness for use.A15 I0 - U.S. Census count variables such as
TOTPOandP20 HHPOare complete counts and do not have correspondingP20 MOEandRELfields.
Here are some more considerations with GeoEnrichment usage on ACS or Census 2020 data -
- ACS data is based on a continuous rolling sample and is updated annually. Because ACS values are estimates rather than complete counts, they are often accompanied by MOE and REL fields.
- Census 2020 data is based on a full population count collected every 10 years. It provides point-in-time counts for population and housing characteristics.
Learn more about ACS and demographic data from the American Community Survey (ACS) data documentation and the 2020 Census data documentation.
Example Use Cases
- Retail analysts can enrich store catchment areas with demographic data to inform marketing strategies.
- Urban planners can append population and housing variables to city districts for resource allocation.
- Insurance companies can enrich property polygons with risk-related variables for better underwriting.