Abstract
Rural settlement is the basic spatial unit for compact communities in rural area. Scientific exploration of spatial-temporal differentiation and its influencing factors is the premise of spatial layout rationalization. Based on land use data of Liangshan Yi Autonomous Prefecture (hereinafter referred to as Liangshan Prefecture) in Sichuan Province, China from 1980 to 2020, compactness index, fractal dimension, imbalance index, location entropy and the optimal parameters-based geographical detector (OPGD) model are used to analyze the spatial-temporal evolution of the morphological characteristics of rural settlements, and to explore the influence of natural geographical factors, socioeconomic factors, and policy factors on the spatial differentiation of rural settlements. The results show that: (1) From 1980 to 2020, the rural settlements area in Liangshan Prefecture increased by 15.96 km2. In space, the rural settlements are generally distributed in a local aggregation, dense in the middle and sparse around the periphery. In 2015, the spatial density and expansion index of rural settlements reached the peak. (2) From 1980 to 2020, the compactness index decreased from 0.7636 to 0.7496, the fractal dimension increased from 1.0283 to 1.0314, and the fragmentation index decreased from 0.1183 to 0.1047. The spatial morphological structure of rural settlements tended to be loose, the shape contour tended to be complex, the degree of fragmentation decreased, and the spatial distribution was significantly imbalanced. (3) The results of OPGD detection in 2015 show that the influence of each factor is slope (0.2371) > traffic accessibility (0.2098) > population (0.1403) > regional GDP (0.1325) > elevation (0.0987) > poverty alleviation (0). The results of OPGD detection in 2020 show that the influence of each factor is slope (0.2339) > traffic accessibility (0.2198) > population (0.1432) > regional GDP (0.1219) > poverty alleviation (0.0992) > elevation (0.093). Natural geographical factors (slope and elevation) are the basic factors affecting the spatial distribution of rural settlements, and rural settlements are widely distributed in the river valley plain and the second half mountain area. Socioeconomic factors (traffic accessibility, population, and regional GDP) have a greater impact on the spatial distribution of rural settlements, which is an important factor affecting the spatial distribution of rural settlements. Policy factors such as poverty alleviation relocation have an indispensable impact on the spatial distribution of rural settlements. The research results can provide decision-making basis for the spatial arrangement of rural settlements in Liangshan Prefecture, and optimize the implementation of rural revitalization policies.
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Availability of Data/Materials: The datasets generated during this study are available from the corresponding author upon reasonable request and within the framework of cooperation agreements and scientific research projects.
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This research was funded by the National Natural Science Foundation of China (Grant Nos. 41971015), and Doctoral research program of China West Normal University (Grant Nos.19E067). The author wishes to thank academic editors and anonymous commentators for their valuable suggestions and comments, and all the author contributed to this article.
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WANG Yumeng: Conceptualization, Methodology, Formal analysis, Investigation, Resources, Data curation, Writing-original draft, Writing-review & editing, Visualization. DENG Qingchun: Conceptualization, Methodology, Writing-original draft, Writing-review & editing, Supervision, Project administration, Funding acquisition. YANG Haiqing: Writing-review & editing, Supervision. LIU Hui: Validation, Investigation, Supervision. YANG Feng: Software, Formal analysis, Resources. ZHAO Yakai: Software, Validation, Resources.
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Wang, Y., Deng, Q., Yang, H. et al. Spatial-temporal differentiation and influencing factors of rural settlements in mountainous areas: an example of Liangshan Yi Autonomous Prefecture, Southwestern China. J. Mt. Sci. 21, 218–235 (2024). https://doi.org/10.1007/s11629-023-8191-6
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DOI: https://doi.org/10.1007/s11629-023-8191-6