Impacts of point of interest (POI) data selection on 15-Minute City (15-MC) accessibility scores and inequality assessments

Abstract

The 15-minute city (15-MC) concept, which is gaining attention among urban planners and researchers worldwide, focuses on strategically placing essential amenities within 15-minute walking or biking distances. When evaluating cities’ existing 15-MC accessibility or other variants of chrono-urbanism, previous studies have largely relied on open-source datasets, such as OpenStreetMap (OSM), which are often criticized for their limited point of interest (POI) data quality. This raises concerns about unreliable evaluations of 15-MC accessibility. Using geospatial analysis methods to calculate 15-MC accessibility scores in six differently-sized regions in Virginia, United States, this study empirically compares OSM’s point datasets with its less contentious alternative, Google Maps data. In four of our study areas, the average 15-MC accessibility scores obtained from the OSM’s point-based POI data were significantly lower than those obtained from Google POI data. Furthermore, the results show that the overall inequality (measured by Gini indices) deviates from the standard range of Google-based values when the OSM’s point-based POI data is used. These findings raise methodological concerns regarding the inadequate representation of the real world due to the limitations of OSM’s point-based POI data, which may lead to flawed assessments of 15-MC accessibility scores.