Classifying community space at a historic site through cognitive mapping and GPS tracking: The case of Gulangyu, China

Local community space at historic sites is easily unsettled by the flood of numerous tourists, but arguably the negative impacts of hard tourism on community spaces are even more severe. Understanding the situation and seeking appropriate optimization strategies to balance urban tourist development and community space protection has gradually become a commonly desired norm amongst researchers and practitioners alike. Nevertheless, as investigators have suggested, the construction of this balance is often very difficult and actual workable and practical solutions to real problems are often still rare. Part of the reason for a lack of workable solutions lies in the difficulties of understanding conflicting space. This article adopts a quantitative approach to identify various types of community spaces, by overlaying cognitive maps of the local community with data on the behavioral patterns of tourists via GPS tracking. Based on the classification of various kinds of community spaces, a series of corresponding optimization strategies to protect various communities are proposed. To conclude, this article explores new analytical frameworks for the sustainable development of historic sites by the classification of community spaces, via a combination of cognitive mapping, GPS tracking, and GIS visualization methods.