Rural Resilience Evaluation and Influencing Factor Analysis Based on Geographical Detector Method and Multiscale Geographically Weighted Regression

• Published in: Land
• Main Authors: Huimin Wang, Yihuan Xu, Xiaojian Wei
• Format: Article
• Language: English
• Published: MDPI AG 2023-06-01
• Subjects: rural resilience; rural revitalization; geographic detector; multiscale geographically weighted regression (MGWR)
• Online Access: https://www.mdpi.com/2073-445X/12/7/1270

Resilience evaluation is an important foundation for sustainable rural development. Taking the 57 counties in Guangdong province as examples, this study used the CRITIC method to construct a comprehensive evaluation index system for rural resilience and identified the main influencing factors and their spatial heterogeneity on the basis of the geographical detector method and multiscale geographically weighted regression. The results showed that: (1) Most of the counties in Guangdong province had medium or higher values of comprehensive resilience, and the high-value areas were mainly located in the Pearl River Delta region. (2) The comprehensive resilience and each dimensional resilience measure exhibited significant positive spatial correlations. (3) The geographic detector results showed that the per capita gross regional product and the number of industries above the scale were the main influencing factors for rural resilience, and each influencing factor had an enhanced effect after interaction. (4) The effect of each factor on rural resilience demonstrated spatial heterogeneity. Specifically, the proportion of secondary and tertiary industries showed negative effects in some counties in eastern and northern Guangdong and positive effects in other counties.