Integrating Objective Spatial Data and Subjective Perceptions through GIS-Supported Citizen Science for a holistic Urban Walkability Assessment

This study presents a holistic walkability assessment framework that integrates objective spatial indicators with subjective perceptions, focusing on micro-scale features such as sidewalks, crossings, and pedestrian infrastructure. Using Serres’ Central Park as a case study, it applied a mixed-methods approach combining geospatial analysis, georeferenced app data, and geolocated post-hoc questionnaires across selected walking routes. Objective indicators like infrastructure quality and safety were mapped using Google Street View, while pedestrian stressors were recorded through Citizen Science methods. The spatial analysis identified key divergences between infrastructural conditions and pedestrian experiences, revealing that objective measures alone may not fully reflect perceived walkability. These findings underscore the importance of incorporating experiential factors into walkability assessments. The proposed framework offers a practical and adaptable tool for urban planners and researchers, enabling more nuanced, human-centred evaluations of pedestrian environments and supporting the development of inclusive, accessible urban mobility strategies.