Spatial Connectivity and Development Potential of Traditional Villages in Clustered Areas: A Case Study of Qiandongnan Prefecture
Year: 2025
Type: article
Abstract: Traditional villages, as forms of significant cultural heritage, have garnered global scholarly attention. This study focuses on the traditional village clusters in Qiandongnan Prefecture, a UNESCO World Heritage site, which includes 415 nationally designated villages. Based on spatial relational analysis and other methods, this study explores the intrinsic relationship between the spatial connectivity of traditional village clusters and their development. The findings are as follows: 1. The spatial distribution of villages exhibits a “dense core, sparse periphery, and localized jumps” pattern. 2. There are five types of development, with over 70% based on agriculture and low industrial differentiation. 3. The spatial connectivity network is clustered, with overall connectivity but a lack of internal coherence, forming a hierarchical network constrained by geography. 4. The spatial connectivity is relatively unstable, highly vulnerable, and exhibits a clear core-periphery structure, where geographical proximity determines basic connections and functional uniqueness drives value-added connections. 5. The overall development potential of these villages is assessed as medium to low. Enhancing network connectivity can foster comprehensive development, and adjusting spatial connectivity could improve its development potential. The study proposes a two-tiered optimization strategy based on the intrinsic connectivity and development characteristics of these villages, providing insights into the development of traditional villages in other regions and cultural heritage areas worldwide.
Source: Land
DOI: 10.3390/land14101929
Authors: Jinyu Fan, Bohong Zheng, Huayan Yuan, Boyang Zhang, Piao Zhang
Institutions: Central South University, Guizhou University, Guiyang University
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,137
Funder: National Science Foundation
OpenAlex ID: W4414438240
