Spatiotemporal behavior pattern differentiation and preference identification of tourists from the perspective of ecotourism destination based on the tourism digital footprint data.

Tourist impact management in ecotourism destinations requires an accurate description of tourists' spatiotemporal behavior patterns and recreation preferences to minimize the ecological environmental impact and maximize the recreation experience. This study classified tourist behaviors into five typical behavior patterns based on the digital footprints of tourists visiting Ziwuyu of the Qinling Mountains, including 348 traveling tracks and 750 corresponding geotagged photographs: short-distance, traversing, reentrant, large loop, and small loop. Furthermore, each behavior pattern's recreation preference was identified using photograph analysis. Tourists with large-loop and reentrant behavior patterns have 89.8% and 30% chances of visiting Jianshanding, respectively. Key protected areas are faced with the risk of ecological environmental damage. Based on the behavior pattern differentiation and preference of tourists, this paper provides a decision-making basis for the classified management and guidance of tourists in ecotourism destinations. It has reference value for the management of similar ecotourism destinations.