Pedestrian mobility citizen science complements expert mapping for enhancing inclusive neighborhood placemaking

Abstract

Cities are complex systems that demand integrated approaches, with increasing attention focused on the neighborhood level. This study examines the interplay between expert-based mapping and citizen science in the Primer de Maig neighborhood of Granollers, Catalonia, Spain--an area marked by poor-quality public spaces and long-standing socio-economic challenges. Seventy-two residents were organized into 19 groups to record their pedestrian mobility while engaging in protocolized playful social actions. Their GPS identified opportunity units for meaningful public space activation. Although 56% of observed actions occurred within expert-defined units, the remaining 44% took place elsewhere. Clustering analysis of geo-located action stops revealed seven distinct clusters, highlighting overlooked areas with significant social potential. These findings underscore the complementarity of top-down and bottom-up approaches, demonstrating how citizen science and community science approaches enriches urban diagnostics by integrating subjective, community-based perspectives in public space placemaking and informing inclusive, adaptive sustainable urban transformation strategies.

Figures (3)

• Figure 1: Identification of opportunity units with cartographic expert-based mapping. (a) Intersection of the three maps—the visual, spatial, and social dimensions—revealing eight areas with high appropriability potential by the residents. Darkest areas are the most promising ones. (b) The eight areas of appropiability (opportunity units, OUs) with their code-name. C01, C02, C03 and C04 correspond to inner areas of the neighborhood while P01, P02, P03 and P04 operate as portals, due to their capacity to redistribute pedestrian flow the neighborhood. (c) Map of the neighborhood in white with the eight OUs. The Primer de Maig neighborhood in Granollers, Catalonia, Spain, covers an area of 3 hectares (300 meters by 100 meters approximately).
• Figure 2: Spatial distribution and trajectories of participant groups in the citizen science exploratory pedestrian mobility experiment. (a) Heatmap of all recorded GPS positions. (b) Trajectories of the 19 participant groups. In both visuals, the black perimeter outlines the Primer de Maig neighborhood. The map is rendered using the OpenStreetMap layout.
• Figure 3: Location of the 68 action stops within the neighborhood. (a) The eight opportunity units (OUs) independently defined by the urban experts correspond to the blue areas. The yellow dots are the locations of the 68 stops. The bigger they are, the longer the stop duration. (b) The seven clusters of stops applying the weighted $K$-means algorithm. For visualization purposes, all stops are represented with bubbles of the same size. Each cluster uses a different color. The map is rendered using the OpenStreetMap layout.