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Mapping Systematically Neglected Neighborhoods: a New York City Case Study

Author(s)

Xinhao Wang

Affiliation(s)

Xi’an Jiaotong-Liverpool University, Suzhou, China

Abstract

Cities now release large volumes of open government data, which promises greater transparency and accountability. However, publishing data does not by itself tell us whether public services and environmental burdens are shared fairly across a city. This paper presents a reproducible framework for measuring spatial equity using only free and public data. The framework joins three sources at the census tract level: resident service requests from a city 311 system, demographic and income data from the United States Census American Community Survey, and environmental burden indicators from the United States Environmental Protection Agency EJScreen tool. From these we build tract level measures of service responsiveness, environmental burden, and social vulnerability, and we use spatial statistics to find tracts where high burden, slow service, and high vulnerability occur together. We call these tracts systematically neglected. We then apply the service part of the framework to New York City, using one partial year of 311 records from 2025. The run produces tract level maps of complaint volume, average resolution time, unresolved rate, and a combined neglect score, and it flags the twenty five most neglected tracts. The result is informative in an unexpected way. Most flagged tracts fall in Manhattan, which is the wealthiest borough, because the score includes complaint volume and volume tracks the propensity to report rather than true need. This is a live example of the reporting bias that the 311 literature describes, and it shows in practice why raw complaint volume must not be read as a sign of neglect. We discuss how to correct this by down weighting volume and by adding the environmental and demographic layers. We also discuss the removal of EJScreen from the EPA website in 2025 and its volunteer reconstruction, which makes data preservation part of equity work. The framework can be applied to any city that runs a 311 system.

Keywords

Environmental Justice; Spatial Equity; Open Government Data; 311 Service Requests; Reporting Bias; Spatial Autocorrelation; Urban Informatics

References

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