A Pilot Study of Sidewalk Equity in Seattle Using Crowdsourced Sidewalk Assessment Data

TL;DR

This study explores sidewalk equity in Seattle by analyzing crowdsourced data to understand how sidewalk quality varies with demographic and urban factors, highlighting the potential and limitations of citizen-generated data for urban planning.

Contribution

It demonstrates the feasibility of using large-scale crowdsourced sidewalk data for spatial equity analysis in urban environments.

Findings

Sidewalk quality varies with racial and income demographics.

Crowdsourced data can reveal spatial disparities in sidewalk conditions.

Limitations include data noisiness and coverage gaps.

Abstract

We examine the potential of using large-scale open crowdsourced sidewalk data from Project Sidewalk to study the distribution and condition of sidewalks in Seattle, WA. While potentially noisier than professionally gathered sidewalk datasets, crowdsourced data enables large, cross-regional studies that would be otherwise expensive and difficult to manage. As an initial case study, we examine spatial patterns of sidewalk quality in Seattle and their relationship to racial diversity, income level, built density, and transit modes. We close with a reflection on our approach, key limitations, and opportunities for future work.