Driving Force–Pressure–State–Impact–Response-Based Evaluation of Rural Human Settlements’ Resilience and Their Influencing Factors: Evidence from Guangdong, China

During urbanization, rural human settlements experience dual pressures from both ecology and culture. Strengthening resilience can enhance the system’s ability to withstand external pressures and restore equilibrium, providing a new research perspective and practical approach for the sustainable development of rural areas. Yet, there are limited reports in the literature on evaluating and improving rural human settlements resilience. To fill this gap, the paper establishes an evaluation system utilizing the DPSIR framework and entropy method. It employs 115 counties and districts in Guangdong Province as samples to evaluate rural human settlements’ resilience in 2020. The Geographically Weighted Regression (GWR) model is used to analyze spatial differences and the influencing mechanisms of various factors on resilience. The results suggest that the overall rural human settlements’ resilience in Guangdong Province is relatively low, showing a concentrated spatial distribution and also variations in the levels and spatial distributions of resilience across different dimensions. Moreover, various dimensions of resilience significantly impact rural human settlements. The driving force resilience coefficients are all significantly positive, with higher values in Western Guangdong and Eastern Guangdong. The pressure resilience coefficients are all significantly negative, decreasing from east to west. The state resilience coefficients show an overall positive correlation, with lower values in the central and northern parts and higher values in the eastern and western parts. The impact resilience and response resilience coefficients are generally positive, with higher values in the Pearl River Delta. This paper extends the theoretical framework for evaluating and analyzing rural human settlements’ resilience, offering empirical evidence to optimize their resilience in a geographical context.