❮ Projects page Transportation Alternatives

Spatial Analysis Project:

While recent national studies have found that traffic crashes occur at disproportionately higher rates in low-income and high-poverty neighborhoods, TransAlt is interested in examining whether this statement holds true in New York City. Understanding who is most affected will help inform policy as we work to achieve Vision Zero – the Mayor’s goal of zero traffic deaths and serious injuries, and to achieve a more equitable city. In order to make the strongest possible case for interventions from lawmakers and city agencies, we need strong data analysis.

The goal of this project is to examine the correlation between poverty level and crash density in New York City. Using community board-level income and poverty data and NYPD crash statistics as data sources, this spatial analysis will determine whether New York City’s low-income neighborhoods experience disproportionately higher injuries or fatalities due to traffic crashes.

Data available:

We have access to all the data for this project, including:

• Geocoded traffic crash data publicly available via the NYPD Motor Vehicle Collisions open data portal
• Income/poverty level data publicly available via the 2011-2013 U.S. Census Bureau’s American Community Survey for each community board in NYC
• Relevant community board statistics such as population and square mileage via the NYC Department of City Planning’s Community Portal
• Shapefile and dataset exports, etc.

Maps and Reports that will be created:

We anticipate that the fellow will produce a series of calculations, maps and analyses we will use to publish a comprehensive report:

1. Spreadsheet aggregating crashes in each community board with income/poverty data, normalized by population size and square-mileage. The spreadsheet would rank community boards by the percentage of each population living below the poverty-level borough-wide and citywide.
2. Maps illustrating crash density by income/poverty citywide and borough-wide. We would also like maps of community boards with strong correlations between crash density and income. We envision a “heat map” format but are also interested in any other creative data visualization ideas.
3. Beyond these outcomes, we’d like a short report including initial analysis of these findings.

How the maps and reports will be used:

We will build on the fellow’s analysis to produce a full-length report exploring the connection between income and crash density. The report will be published on the TransAlt website, distributed to press, and used to inform briefings to policymakers in the City Council and the state legislature to shape policy. Our organization has been at the forefront of Vision Zero and is highly influential thanks to our emphasis on evidence-based policymaking, to which the Fellow’s work will contribute. This analysis will help shape the city’s investment in transportation infrastructure, ultimately bringing us closer to eliminating traffic deaths/injuries, and creating a more equitable city.