Multi-scale spatial differentiation and formation mechanisms of rural settlements (RS): a Geodetector-based analysis in the middle-lower yellow river basin (ML-YRB), China
Focusing on the core issue of the multi-scale characteristics and driving mechanisms of spatial differentiation of rural settlements (RS) in the middle-lower Yellow River Basin (ML-YRB), this study aims to provide a scientific basis for the development and protection of regional RS. Using nearest ne...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-07-01
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| Series: | Frontiers in Environmental Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2025.1606333/full |
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| Summary: | Focusing on the core issue of the multi-scale characteristics and driving mechanisms of spatial differentiation of rural settlements (RS) in the middle-lower Yellow River Basin (ML-YRB), this study aims to provide a scientific basis for the development and protection of regional RS. Using nearest neighbor analysis, kernel density estimation and spatial autocorrelation, the study systematically reveals the spatial distribution patterns and scale-dependent differences of RS in ML-YRB at city, county, and town scales. Furthermore, geographic detectors are employed to quantitatively evaluate the explanatory power of natural geographical and socio-economic factors for RS spatial differentiation. The results show that: (1) In ML-YRB, RS shows clear spatial clustering, concentrating in areas with gentle slopes, low altitudes, favorable thermal humid conditions, and high agricultural potential. (2) RS clustering varies across scales. The Moran’s I values are 0.79, 0.75, and 0.81 at city, county, and town scales. (3) Geographical environment, location conditions, and socio-economic factors together shape the spatial pattern of RS in ML-YRB. Specifically, lower and flatter terrain, soil more suited to farming, and proximity to rivers and lakes are linked to denser settlements. Also, areas near cities and roads show a clear RS agglomeration effect. (4) Key factors affecting the spatial distribution of RS have been quantitatively identified: soil type, population density, water proportion, topographic undulation, road network density, and distance from the central town. These findings offer a direct basis for creating tailored spatial policies for RS development in ML-YRB. |
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| ISSN: | 2296-665X |