Objectively Measuring Urban Streetscape Perceptions from Different Perspectives : Better Identifying Street Regeneration Priorities in Urban Renewal

The measurement of urban streetscape quality facilitates the identification of street regeneration. The emerging Street View image and semantic segmentation have recently proven assistance for investigating urban spatial quality. However, current studies using Google Street View (GSV) cannot explicitly reflect pedestrian perceptions, as GSVs are taken from a driveway perspective, which differs from the pedestrian view. This study aims to elucidate the variance in quantitative measurements of streetscape perceptual qualities under different viewpoints and to identify the priority of street renewal based on a combined analysis between street perceptual quality and pedestrian potential. We collected GSVs and self-photographed pedestrian views in the center of Düsseldorf. 5,300 images are gathered, and their semantic information at the pixel level is extracted by the segmentation technique DeepLab V3+. The results indicate that perspective differences have varying geographic effects on street perceptions, with the most significant effect on walkability. In addition, the combined analysis identifies renewal areas and provides planning techniques and operational standards for urban functional zones, streets, and street segments, respectively. The joint spatial syntax and image segmentation-driven approach offers a feasible paradigm for identifying fine-grained built environments and urban renewal. In short, this study promotes human-centered urban measurement and spatial research