Accessible Path Finding for Historic Urban Environments: Feature Extraction and Vectorization from Point Clouds

A novel method for generating accessible sidewalk networks in historic urban environments, such as UNESCO World Heritage Sites, achieves over 98% vectorization accuracy. This approach leverages point cloud data to semantically segment sidewalks and roads, enabling precise extraction of physical and geometric attributes without relying on traditional cartographic data or crowdsourcing. The resulting vector layer facilitates the computation of accessible paths between Points of Interest using QGIS, as demonstrated in a case study of Sabbioneta, Italy. This method offers potential applications for city planners and developers of routing apps, enhancing urban accessibility while preserving historical integrity.

Treccani, D., Díaz-Vilariño, L., & Adami, A. (2022). ACCESSIBLE PATH FINDING FOR HISTORIC URBAN ENVIRONMENTS: FEATURE EXTRACTION AND VECTORIZATION FROM POINT CLOUDS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLVI-2/W1-2022, 497–504. https://doi.org/10.5194/isprs-archives-xlvi-2-w1-2022-497-2022