Spatial Complex Morphological Evolution and Influencing Factors for Mountain and Seaside Resort Tourism Destinations

Abstract EN

Spatial restructuring of tourism destinations is important not only for optimizing the spatial structure but also for promoting its sustainable development.

This study adopted participatory rural assessment (PRA), GIS spatial analysis, and Google Earth remote sensing images as the main research methodology.

The case studies of mountain resort destination, Huangshui Town, and seaside resort destination, Jinshitan, were analyzed.

The study contributes to complex morphological evolution from the perspectives of external structure expansion and internal function reconstruction, revealing the spatial characteristics and explaining the influencing factors.

The results showed that (1) in the process of tourism development, these two places have experienced large-scale growth of construction land and expansion of spatial scope.

The external spatial structure of Huangshui Town is concentrated in the center and is scattered outward, changing from the form of a strip to a radiating pattern and finally to clusters.

The spatial layout of Jinshitan has shifted from scattered to concentrated, changing from scattered to a strip along the coastline.

(2) In particular, the internal functional structures of the two places have transitioned from a single residential function to a multicomposite function that integrates accommodation, dining, and entertainment.

Among them, Huangshui Town is an “axial belt + group type” structure, and Jinshitan is a “wave type” structure.

(3) The results also showed that natural factors such as traffic, terrain, rivers, lakes, and coastlines and anthropogenic factors such as government intervention and community participation are the main factors affecting the evolution of the spatial form of tourism destinations.

The two tourist destinations in the study represent mountain resort type and coastal resort type, thereby showing that the spatial structure evolution model has certain typicality and representativeness.