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.

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