Analysis of spatial characteristics and influence mechanism of human settlement suitability in traditional villages based on multi-scale geographically weighted regression model: A case study of Hunan province

Abstract

Traditional villages are invaluable cultural heritage sites in China, reflecting a rich historical and cultural legacy. However, rapid urbanization has led to the destruction and loss of numerous traditional villages. The remaining traditional villages also face challenges in preserving their original living environment. In order to assess human settlement suitability and identify potential factors, this paper proposes a village-scale model for assessing human settlement suitability. This paper used an eight-factor evaluation system, multi-criteria decision analysis and spatial visualization methods to evaluate the scores and spatial characteristics of human settlement suitability of 688 traditional villages in Hunan Province. This paper also examines the factors affecting cluster suitability using geographic detectors and multi-scale geographically weighted regression (MGWR) models. This study found that the quality of human settlement suitability varied widely. The overall quality is low and very few areas achieve medium or higher scores. Among them, the traditional villages in Huaihua city, Zhangjiajie junction, southern Hengyang city, northwestern Yongzhou city, central Chenzhou city and Changsha city exhibit higher scores. Secondly, the commercial facility density and normalized difference vegetation index (NDVI) are important factors driving the spatial changes. And there is a significant interaction effect between them. Additional factors impacting spatial variation include annual average temperature, per capita disposable income, and average house price. This comprehensive assessment reveals spatial characteristics and potential influencing factors. The results of the study provide an empirical basis and decision-making foundation for the protection and development of traditional villages, which will ultimately contribute to the sustainable development of China's rural areas.