Seasonal dynamics of hiking activities in mountainous areas: a topography-aware sequential network modeling approach using crowdsourced trajectories

Abstract

The growing popularity of hiking has intensified the interaction between urban areas and wilderness landscapes, highlighting the need for spatially-explicit models to quantify trail usage dynamics and alleviate ecological pressures in mountainous regions. This study investigates spatiotemporal hiking patterns in China’s Qinling Mountains (2020–2023) using crowdsourced GPS trajectories collected from outdoor sports Apps. The paper proposes a topography-aware sequential network model that accounts for terrain resistance and incorporates behaviorally significant feature points, enabling detailed analysis of seasonal dynamics in hiker movement patterns on informal trails in mountainous areas. Based on the network, the complex network analyses, we identify hiking hotspots, core hubs and critical paths, reveal the popular routes within network communities, and reconstruct the evolution of these communities over time. Key findings include: (1) three elevation-specific activity zones (at 1000 m, 2000 m, and 3500 m), (2) a significant increase in short-distance hiking activities. (3) 62 % of trails being used exclusively in a single season, and (4) summer networks showing superior connectivity. The discussion highlights strategies to balance ecological conservation with hiking tourism development, including key path management, regulation of seasonal visitor flows, and evidence-based planning for transportation infrastructure. These findings offer actionable insights for sustainable tourism, contributing to GIS-driven frameworks that promote human-nature coexistence in mountain ecosystems.