Developing sidewalk inventory data using street view images

Abstract

(1) Background: Public sidewalk GIS data are essential for smart city development. We developed an automated street‐level sidewalk detection method with image‐processing Google Street View data. (2) Methods: Street view images were processed to produce graph‐based segmentations. Image segment regions were manually labeled and a random forest classifier was established. We used multiple aggregation steps to determine street‐level sidewalk presence. (3) Results: In total, 2438 GSV street images and 78,255 segmented image regions were examined. The image‐level sidewalk classifier had an 87% accuracy rate. The street‐level sidewalk classifier performed with nearly 95% accuracy in most streets in the study area. (4) Conclusions: Highly accurate street‐level sidewalk GIS data can be successfully developed using street view images.