A Data-Driven Framework for Health-Promoting Trail Network Planning Using Multi-Source Geospatial Data: Evidence from Qingdao, China

Health-promoting trail (HPT) networks can provide spatial support for walking-based physical activity and healthy city development. Yet existing planning approaches often address environmental suitability or route optimization without fully integrating spatial continuity, network generation, and service potential. This study develops a data-driven framework for HPT network planning using multi-source spatial data (MSSD), with the eastern urban area of Qingdao, China, as a case study. Previously published choice-based conjoint (CBC) preference estimates were used to weight eight environmental indicators in a geographic information system (GIS) to calculate a fitness suitability index (FSI). Connection nodes were linked by routes minimizing the length-weighted inverse FSI, and urban spaces with high continuity potential were incorporated as planning corridors. The generated network’s service potential was evaluated through Euclidean proximity coverage of residential locations and estimated population, together with network length within residential proximity buffers. The spatial assessment identified limited provision of long continuous walking segments in the existing walking network. The proposed integration identified opportunities for longer continuous walking corridors and extensive potential residential coverage. By linking preference-informed assessment, geospatial network generation, and service potential evaluation, the framework supports sustainable urban planning by identifying opportunities to coordinate existing urban spatial resources for health-promoting walking infrastructure.