Spatial behavioural characteristics and pattern recognition of hikers in national parks: evidence from GPS trajectory data

Studying hikers’ spatial behaviour in national parks is vital to enhancing recreational experiences, optimising resource allocation, and promoting sustainable development. However, research on the spatial behaviour of hikers in national parks remains limited. Based on GPS trajectory data, this study constructs a comprehensive framework integrating temporal and spatial distribution analysis, stay area identification, and spatial behavioural pattern mining to systematically reveal the spatial behavioural characteristics and patterns of hikers in national parks. The research first finds that hiking activities exhibit cyclical and concentrated characteristics in temporal and spatial distribution. Through a two-stage clustering algorithm, stay areas are then identified, revealing the associations between stay behaviour and environmental factors. Based on the identified stay areas, our proposed spatial behavioural pattern mining method categorises hikers’ spatial behaviour in national parks into four types, which are defined as popular classic hiking pattern, easy recreational hiking pattern, unique niche hiking pattern, and professional challenge hiking pattern, reflecting the diversity and regularity of hiker behavioural choices. This research fills the gap in data-driven analysis of hiking behaviour in national parks, provides new perspectives for understanding the interactions between hikers and natural environments, and offers scientific evidence for differentiated management and sustainable development of national parks.