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<p>As a central hub on the Qinghai–Tibet Plateau, Lhasa exhibits unique rural settlement patterns shaped by harsh high-altitude environments, economic disparities, and profound socio-cultural influences. To elucidate the underlying formation mechanisms, this study constructs a “Nature-Economy-Culture” tripartite framework. Using data from 226 villages, we established an integrated workflow encompassing pattern identification, driver detection, and mechanism modeling. Methodologies included spatial statistics, Geodetector, Geographically Weighted Regression (GWR), and XGBoost-SHAP analysis to investigate the influencing factors of settlement distribution. Results show:: (1) The spatial distribution presents a significant differentiation pattern characterized by “two high-density clusters, one axial belt, and multiple scattered points”; (2) Settlement density exhibits significant spatial coupling with natural, economic, and cultural factors; (3) Elevation (<i>q</i> = 0.553), cultural heritage density (<i>q</i> = 0.439) and precipitation (<i>q</i> = 0.216) were identified as the primary determinants driving spatial heterogeneity, demonstrating distinct threshold and mutual enhancement effects; and (4) These factors exert spatially heterogeneous influences, shaping local patterns by modulating the explanatory power of variables across different sub-regions. This study contributes to research on human-land relationships in high-altitude regions and provides a scientific basis for rural spatial optimization and cultural landscape conservation.</p>

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Spatial distribution patterns and influencing factors of rural settlements in Lhasa, Tibet

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月1日

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  • Yibing Xie,
  • Xuan Lei,
  • Yumeng Song,
  • Luyang Zhong,
  • Yingzi Zhang

摘要

As a central hub on the Qinghai–Tibet Plateau, Lhasa exhibits unique rural settlement patterns shaped by harsh high-altitude environments, economic disparities, and profound socio-cultural influences. To elucidate the underlying formation mechanisms, this study constructs a “Nature-Economy-Culture” tripartite framework. Using data from 226 villages, we established an integrated workflow encompassing pattern identification, driver detection, and mechanism modeling. Methodologies included spatial statistics, Geodetector, Geographically Weighted Regression (GWR), and XGBoost-SHAP analysis to investigate the influencing factors of settlement distribution. Results show:: (1) The spatial distribution presents a significant differentiation pattern characterized by “two high-density clusters, one axial belt, and multiple scattered points”; (2) Settlement density exhibits significant spatial coupling with natural, economic, and cultural factors; (3) Elevation (q = 0.553), cultural heritage density (q = 0.439) and precipitation (q = 0.216) were identified as the primary determinants driving spatial heterogeneity, demonstrating distinct threshold and mutual enhancement effects; and (4) These factors exert spatially heterogeneous influences, shaping local patterns by modulating the explanatory power of variables across different sub-regions. This study contributes to research on human-land relationships in high-altitude regions and provides a scientific basis for rural spatial optimization and cultural landscape conservation.