Spatial Differentiation and Driving Force Detection of Rural Settlements in the Yangtze River Delta Region

Ting You and Shuiyu Yan ()
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Ting You: School of Architecture and Urban Planning, Chongqing University, Chongqing 400030, China
Shuiyu Yan: School of Architecture and Urban Planning, Chongqing University, Chongqing 400030, China

Sustainability, 2023, vol. 15, issue 11, 1-18

Abstract: As an economically developed region, the Yangtze River Delta region has undergone earth-shaking changes in its rural settlements due to rapid urbanization. For the optimization and adjustment of rural settlements, it is crucial to disclose their distinguishing spatial features and impelling factors. Taking 307 county-level administrative regions in the Yangtze River Delta region as the research object, this study comprehensively uses the landscape index, nearest neighbor index, Moran index, and spatial hot spot detection system to analyze the spatial differentiation characteristics of rural residential location-scale morphology and reveals its driving factors using the optimal parameters-based geographical detector model. According to the findings, rural settlements in the Yangtze River Delta region exhibit an average nearest neighbor index of 0.7417, a Moran’s I of 1.2993 for the number of patches (NP), and a maximum patch density (PD) of 17.25 villages per square kilometer. It has significant characteristics of large-scale village cluster distribution, and the morphology of rural settlements in the southern and northern regions shows apparent differences. The natural environment and social economies, such as elevation, slope, precipitation, and population density, mainly drive the location-scale morphological spatial distribution of rural settlements. At the same time, the interaction between the natural environment, social economy, and location condition factors has a synergistic enhancement effect on the spatial distribution of location-scale morphology of rural settlements.

Keywords: rural settlements; spatial distribution characteristics; geographical detector; Yangtze River Delta region (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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