Scaling Pedestrian Crossing Analysis to 100 U.S. Cities via AI-based Segmentation of Satellite Imagery

TL;DR

This paper presents a scalable AI-based method to automatically measure pedestrian crossing distances across 100 U.S. cities using satellite imagery, achieving high accuracy and revealing regional urban design patterns.

Contribution

It introduces a novel, scalable approach combining satellite imagery, segmentation, and edge detection to measure crossing distances accurately at city scale.

Findings

Achieved 93% accuracy in measuring crossing distances

Median crossing distances range from 32 to 78 feet across cities

Wider crossings correlate with older city incorporation dates

Abstract

Accurately measuring street dimensions is essential to evaluating how their design influences both travel behavior and safety. However, gathering street-level information at city scale with precision is difficult given the quantity and complexity of urban intersections. To address this challenge in the context of pedestrian crossings - a crucial component of walkability - we introduce a scalable and accurate method for automatically measuring crossing distance at both marked and unmarked crosswalks, applied to America's 100 largest cities. First, OpenStreetMap coordinates were used to retrieve satellite imagery of intersections throughout each city, totaling roughly three million images. Next, Meta's Segment Anything Model was trained on a manually-labelled subset of these images to differentiate drivable from non-drivable surfaces (i.e., roads vs. sidewalks). Third, all available crossing edges from OpenStreetMap were extracted. Finally, crossing edges were overlaid on the segmented intersection images, and a grow-cut algorithm was applied to connect each edge to its adjacent non-drivable surface (e.g., sidewalk, private property, etc.), thus enabling the calculation of crossing distance. This achieved 93 percent accuracy in measuring crossing distance, with a median absolute error of 2 feet 3 inches (0.69 meters), when compared to manually-verified data for an entire city. Across the 100 largest US cities, median crossing distance ranges from 32 feet to 78 feet (9.8 to 23.8m), with detectable regional patterns. Median crossing distance also displays a positive relationship with cities' year of incorporation, illustrating in a novel way how American cities increasingly emphasize wider (and more car-centric) streets.