Utilizing the network to optimize the mismatch between supply and demand of recreational services: a case study of Guangdong-Hong Kong-Macao Greater Bay Area

The spatial mismatch between urban ecological spaces and residential areas, combined with rapidly increasing demand for nature-based recreation, has intensified the mismatch between the supply and demand of recreational services. Existing studies often optimize resource allocation based on the static spatial pattern of recreational supply–demand matching, while largely overlook the potential of recreational networks to improve recreational service supply–demand relationships. Taking the Guangdong–Hong Kong–Macao Greater Bay Area as a case study, this research develops an optimization framework that leverages recreational networks to alleviate supply–demand mismatches in recreational services. The framework identifies recreational supply and demand sources based on mapped service supply and deficits, constructs a recreational network, and overlays it with deficit patterns to extract deficit-optimized corridors (DOCs). The results show that: (1) Recreational services reflect a significant imbalance in the spatial distribution of supply and demand, with deficit, balance, and surplus zones accounting for 8.50%, 12.10%, and 79.40% of the area; (2) A total of 426 recreational supply sources and 63 recreational demand sources were identified, with considerable variation in distribution patterns among cities; (3) We delineated 1199 recreational connectivity corridors and 402 recreational orientation corridors, showing a radial distribution with dense and short corridors in central areas and longer corridors in peripheral zones, demonstrating strong network connectivity; (4) In total, 1579 DOCs were identified, spanning 1895.04 km and covering 72.42% of the supply-demand deficit area. This proposed framework enhances the spatial continuity and stability of recreational services provision and provides theoretical and practical support for urban spatial planning and refined management.