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July 1, 2026Land0 citationsOpen Access

Spatiotemporal Evolution and Influencing Factors of Rural Settlements in a Metropolitan Hinterland: A Case Study of Changsha County, China

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FJFan JiaSHShuyi HuSLS Y Lei

Key Points

  • This research aims to examine the evolution of rural settlements and the influencing factors in metropolitan hinterlands.
  • Integrated landscape pattern indices, kernel density estimation, centroid migration analysis, OPGD, and GWRF.
  • Analyzed data from 1990 to 2020 in Changsha County.
  • Identified factors influencing spatial differentiation of rural settlement scale in 2020.
  • Rural settlement area increased by 69.7% with patch density declining by 26.7%.
  • High-value kernel density zones clustered in the southwest; settlement centroid migrated towards the urban core.
  • Key driving factors include NDVI, secondary and tertiary industry output, with significant spatial heterogeneity in their effects.

Abstract

Metropolitan hinterlands are zones of intense urban–rural factor flows and spatial restructuring, where understanding rural settlement evolution is crucial for revealing human–land relationship transformations. Taking Changsha County, the core hinterland of the Changsha–Zhuzhou–Xiangtan metropolitan area in central China, as a case study, we integrated landscape pattern indices, kernel density estimation, centroid migration, the Optimal Parameters-based Geographical Detector (OPGD), and Geographically Weighted Random Forest (GWRF) to analyze the spatiotemporal evolution of rural settlements from 1990 to 2020 and identify the factors associated with the spatial differentiation of rural settlement scale in 2020. The results showed that: (1) The scale of rural settlements continuously expanded, with the total area increasing by 69.7% while patch density declined by 26.7%, exhibiting a “dense south, sparse north” pattern. High-value kernel density zones progressively clustered toward the southwestern concentric zone, and the settlement centroid persistently migrated toward the urban core. (2) The output value of secondary and tertiary industries per unit area, NDVI, and living facility adequacy were identified as the core driving factors; GDP per capita, distance to cropland, and distance to major roads also exerted notable effects, and strong synergistic interactions were detected among these factors. (3) GWRF-SHAP analysis revealed pronounced spatial heterogeneity: NDVI exhibited a south-promotion, north-suppression bidirectional effect; distance to cropland showed the most stable positive influence; road proximity was significant only at transportation hubs; the output value of secondary and tertiary industries displayed a polarized “central driving, north–south suppression” pattern; and socioeconomic factors generally stimulated expansion in suburban areas while inhibiting it in remote hinterlands. This spatial divergence can be interpreted through the “south-industry, north-agriculture” structure: suburban industrial corridors are associated with externally oriented attraction, whereas remote agricultural hinterlands are more closely related to endogenous, resource-based upgrading. The study proposes a compound explanatory framework of “natural baseline constraints–locational guidance–socioeconomic dominance,” providing a scientific basis for differentiated spatial governance of rural settlements in metropolitan hinterlands.

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Cite This Study

Jia et al. (2026) studied this question.

synapsesocial.com/papers/6a44ae015cd2549c8bc436f3https://doi.org/10.3390/land15071173
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