An Empirical Study on Cluster Distributaries ofthe Initial State of Jiuzhaigou
九寨沟景区初态聚类分流实证研究

Jiuzhaigou is a world renowned nature reserve in the north of Sichuan Province,southwestern China. It is known for many multi-level waterfalls and colorful lakes, and also aUNESCO World Heritage Site in 1992. This has brought enormous tourism resources toJiuzhaigou. In order to realize the sustainable development of the scenic spot, it is of particularsignificance to investigate tourism management and operation of the scenic spot of interest. Basedon simulation of the status quo of operation and analysis of the spatial and temporal characteristicsof the tourist in the midseason, it was concluded that the loads of the scenic spots frequently showan imbalanced state both in time and space. This could be ascribed primarily to inappropriatedivergent behaviors at the initial state. The authors subsequently made an attempt to examine thedistributaries at the initial state to create an equilibration in the loads in the Jiuzhaigou NatureReserve, with the objectives to 1) delivery tourists at the entrance of the valley into scenic areas asquickly as possible and 2) assist in the second diversion to achieve the goal of the load balanceamong scenes using as few vehicles as possible. The authors adopted a stratified clustering methodto classify spots in terms of different scales of tourists at the places of interest. Subsequently, initialdivergent areas and corresponding divergent proportions in terms of their carrying capacity weredetermined. A mathematical model was constructed to optimal the distribution of vehicles at theinitial state. Results indicated that the tourist ratio at the initial state assigned to each area in termsof its carrying capacity is reasonable. This study can provide a basis for balancing the loads ofscenic spots in the system, enhancing the tourism value for tourists, and realizing a coordinatedrelationship between environmental protection and economic growth. Furthermore, it can alsoprovide a basis to realize digital management of the tourism system through examining the steadyflow of tourists and the scheduling rules of resources based on the dynamic forecast of distributionprocesses.