The American Community Survey (ACS) is one of the most important sources of demographic and socioeconomic data in the United States.
It’s produced by the U.S. Census Bureau and updated every year. For anyone working with GIS in the U.S., ACS is essential. It helps map income, education, commuting, internet access, and more—at different geographic levels.
Let’s break down what ACS is, what it offers, and how you can use it in mapping and analysis.
What Is the American Community Survey?
ACS is a continuous survey that collects detailed information from about 3.5 million households each year. It replaced the long-form census in 2010. Instead of waiting every 10 years, we now get annual updates on key social and economic topics.
It provides data at many levels:
- National
- State
- County
- Tract
- Block group (for 5-year estimates)
This makes ACS perfect for localized GIS work.
What Kind of Data Does It Include?
ACS covers a wide range of topics. Some of the most useful categories include:
- Population and age
- Race and ethnicity
- Income and poverty
- Education levels
- Employment and industry
- Housing (type, age, cost)
- Commuting and transportation
- Health insurance
- Internet access
- Language spoken at home
Each data point can be broken down by geography, and often by age, sex, and other groups. This depth is what makes ACS powerful.
ACS Products: 1-Year vs 5-Year
There are two main types of ACS data releases:
1-Year Estimates
- Covers areas with populations of 65,000 or more.
- More current.
- More sampling error.
5-Year Estimates
- Covers all areas, down to block groups.
- More stable and reliable.
- Best for mapping and small-area analysis.
Most GIS projects use the 5-year estimates for better geographic coverage.
Geographic Levels
ACS data is tied to standard Census geographies:
- States
- Counties
- Census tracts
- Block groups
- ZCTAs (ZIP Code Tabulation Areas)
- PUMAs (Public Use Microdata Areas)
This allows direct use in mapping software. You can link ACS data to shapefiles or GeoJSONs using geographic IDs like GEOID. For example: tract GEOID 06075060100 represents a tract in San Francisco County, CA.
Accessing ACS Data
You can get ACS data from several sources:
- data.census.gov – The main platform for table downloads.
- Census API – Useful for direct integration into applications.
- TIGER/Line shapefiles – Boundary files for mapping.
- Census Bureau’s FTP site – Bulk downloads.
- Third-party tools – Like Social Explorer, IPUMS, or PolicyMap.
Some platforms also offer pre-joined ACS + shapefile datasets.
Why ACS Matters in GIS
ACS lets you analyze and map real community characteristics.
Here are some use cases:
Equity Mapping
Map income, housing costs, or health insurance to spot underserved communities.
Urban Planning
Plan transit based on commuting modes or car ownership.
Use housing age and type data to plan development or code enforcement.
Broadband Access
Map internet access levels to support digital equity initiatives.
Environmental Justice
Combine ACS with pollution or flood risk maps to see who’s most exposed.
Public Health
Track poverty or crowded housing to identify vulnerable areas.
Example GIS Projects with ACS
- Mapping school enrollment to plan education services.
- Analyzing where people work and how they get there.
- Identifying food deserts by income and car access.
- Mapping multilingual households for emergency communication planning.
With ACS, you can make maps that tell a human story.
Using ACS in Tools Like Atlas
When working with ACS in a browser-based GIS like Atlas, here are some tips:
- Start with 5-year estimates: for full geographic coverage.
- Use TIGER/Line shapefiles: or join GEOID fields to your own data.
- Normalize values: e.g., use percentages instead of raw numbers to compare across areas.
- Visualize disparities: heat maps of poverty, income, or education show gaps clearly.
- Use margins of error: if making decisions — ACS is survey data, not exact counts.
Limitations to Know
ACS is survey-based. It has sampling error. Especially in small geographies or for detailed breakdowns, the error can be large. Also, ACS data lags. The latest 5-year estimates may include data from 3-5 years ago. Always check the table notes and data quality flags.
