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Li, Q., Cai, X., Li, T., et al. (2024) Research on the Influence of Geographic Distance on Tourist Behavior Based on Social Big Data—Taking Tourists in Huangshan City as an Example. World Geography Research, 33, 175-186.
https://kns.cnki.net/kcms2/article/abstract?v=_Kb8wOrUs9vdiztcfL4DWLGfAHOLPWed0uBI2yZL2gkZPEgI5hhW6DfyvhNawg9ogRHksTY3BmNqWWLvy0uEeH-9FSn3o0vZhFNM4S4lFWKB8ElCBj53DXFbJ807NGTLB4V3UAPjUoFIRZCIALpekg==&uniplatform=NZKPT&language=CHS

has been cited by the following article:

• TITLE: Enhancing Emergency Rescue Capability in Scenic Areas Using Big Data Technology: A Case Study of Mount Tai Scenic Area

  AUTHORS: Tongxing Li, Boye Li, Yongfeng Zhang, Xiaoyu Tan, Zixuan Li

  KEYWORDS: Big Data Technology, Scenic Area, Emergency Rescue, Mount Tai Scenic Area

  JOURNAL NAME: Open Access Library Journal, Vol.11 No.7, July 11, 2024

  ABSTRACT: This study takes Mount Tai Scenic Area as a case study to explore how big data technology can enhance the emergency rescue capability of scenic areas. This paper analyzes the methods and means of using big data technology to improve the emergency rescue capability of scenic spots and the shortcomings in the development and design of emergency rescue system. The research findings indicate that big data technology holds significant potential for application in emergency rescue operations in scenic areas, effectively improving the efficiency and accuracy of the scenic area’s response to emergencies.