How can I use Justice Map?
- Visualize race and income data for your neighborhood, county, state, or the entire US.
- Share a custom map with your friends.
- Journalists, bloggers, activists, and others can create maps for their online or print publications.
- Map makers can add race and income layers to their maps.
- Who Lives Nearby. Advanced mode lets you compare who lives within 1 vs 5 miles of a location (and more!).
Get Support: Email Aaron
with your questions and suggestions.
What data layers do you have?
We have several race layers and income layers (three different
representations of median household income). The race layers are available at the county, census tract, block group, and block level. The income layers
are available at the county and census tract level. This provides greater detail when you zoom in.
What are open map tile layers?
We have 100 GB of map tiles that we are sharing. Similar to open software anyone can use them on their website.
This saves map makers the time required to deal with large datasets and tile production.
What is the data source?
Our information comes from the Census Bureau - the 2010 Census and the latest American Community Survey (five year summary).
How did you create the map?
We imported the census data into a postgis database and generated the tiles with TileMill.
Who is behind this project?
The website was developed by Aaron Kreider - as a project for Energy Justice Network and Sunlight Foundation. Further development has been supported by
the Energy Justice Network and Aaron Kreider (volunteer hours).
Justice Map - open map tile layers for race and income powered by Census Data.
I want you to use the layers on your own map
Sept 19, 2021. If you are using our API, please contact us. Otherwise, as I haven't heard from anyone who is - the API is going to be revised and the old version will break (We might
replace justicemap-api.org with another domain).
Sept 18, 2021. Early release of Census 2020 race data. Income needs to be updated as does the API.
Jan. 14-16, 2020. We updated the income data to use the 2014-2018 American Community Survey.
Jan. 13, 2019. We updated the income data from the 2012-2016 American Community Survey to the 2013-2017 data. This applies to tile layers, clicking on the map,
and the API. Puerto Rico is included in the update! An even bigger change is that we updated the income categories (for the first time),
and started controlling for inflation in the Income Change layer.
Aug 30, 2018. Redesigned the user interface to support mobile phones.
Jan. 9, 2018. We updated the income data from the 2011-2015 American Community Survey to the 2012-2016 data. This applies to tile layers, clicking on the map,
and the API. This time Puerto Rico is included in the update!
Dec. 30, 2016. Try the Spatial Justice Test
. It's a tool to identify environmental injustice (and more). You can
test how race and income varies at different distances from a set of points. Use our power plant data or upload your own!
Dec. 20, 2016. We added a visualization that estimates Income at the Block Level
It can be used as an index that combines race and income to give a micro-level view of environmental injustice (or other forms of spatial injustice).
Dec. 13, 2016. We updated the income data from the 2010-2014 American Community Survey to the 2011-2015 data. This applies to tile layers, clicking on the map,
and the API. Puerto Rico is still using the old data (2007-2011).
- Include the map or data layers on your website
Data and Downloads
Type in a US address, hit 'Submit' and the map will go there.
Lets you save the URL of the current map to make it easier to share.
We have several race data layers that come from the US 2010 census. The Census Bureau uses two main variables - 'race' and 'hispanic'.
- American Indian (only)
- Asian (only) - Does not include Pacific and Hawaiian Islanders.
- Black (only)
- Hispanic- Includes all census races who self-identify as hispanic.
- Non-White - Includes everyone EXCEPT white non-hispanics
- White (only) - White non-hispanics.
- Race and Ethnicity in the US Census
We use Median Household Income from the American Community Survey 2014-2018 five year summary
These income values are estimated and
we show the 90% confidence interval when you click on the map. Income data is only available at the county and census tract levels.
- Income - The default layer uses a differential categorization method that emphasizes the break around the mean.
- Income Rich - a sequential categorization method that emphasizes high income.
- Income Poor - a sequential categorization method that emphasizes low income.
- Income Change - the change in median household income between two five year periods. Currently 2006-2010 vs 2014-2018.
- Income Block - a very experimental estimated income by block. It uses the census tract income, the national difference in median household income by race,
and the race demographics of the block and surrounding blocks to estimate an income. This is intended to be more of a visual tool than a scientific one.
We use the Census 2010 data to calculate population density per square mile. This is available at the county, tract, and block level.
We use four geographical units that come from the Census Bureau.
- County: our largest unit.
- Census Tract: there are 72,000 tracts in the US. Each represents 4,000 people.
- Block Groups: there are 210,000 block groups in the US. Each represents 600 to 3000 people.
- Blocks: there are 8 million blocks in the US. The Census uses a different definition of
block than most people use. Population varies widely due to apartment buildings. Two million blocks have zero people.
Compare the demographics of several areas. You could test if people of a certain income or race are
more likely to be near a location (ex. the site of a proposed waste facility or park).
When you have this featured turned on, it returns the demographics for the area that you last clicked on and compares it to an area within x miles of it.
That radius is chosen based on the map zoom level. You can add your own radius (in miles). You can remove a radius.