Sustainability Assessment and Spatial Optimization of Minority Characteristic Villages Based on the Minimum Cumulative Resistance Model: A Case Study of Qiandongnan, China

The sustainable development of minority characteristic villages (MCVs) is crucial to regional diversity, equality, and inclusion. However, it also faces multi-dimensional challenges, especially spatial imbalance. Taking Qiandongnan, China as a typical case, this study employed multiple methods to assess the sustainability of MCVs. First, this study constructed a comprehensive resistance surface integrating social, economic, and environmental dimensions based on the Minimum Cumulative Resistance (MCR) model and conducted a systematic assessment of the sustainability of MCVs in Qiandongnan. Second, this study evaluated the spatial distribution characteristics of MCV’s sustainability based on the kernel density analysis and the gravity model. Finally, this study proposed a targeted spatial optimization pathway. The results reveal there are significant spatial differences in MCVs; villages in the central, southern, and central-western Qiandongnan exhibit stronger sustainability, whereas the southwest and eastern regions are weak. Seven core villages and one key node were identified. Five sustainable development corridors were established to enhance spatial connectivity. This study provides novel insights for optimizing the spatial governance of MCVs for achieving regional sustainable development and enriches the knowledge body of global rural revitalization.

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Publication Details

Journal
Land
Published
2025-05-27
DOI
https://doi.org/10.3390/land14061154
Citations
1
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
1.11

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article

Sustainability Assessment and Spatial Optimization of Minority Characteristic Villages Based on the Minimum Cumulative Resistance Model: A Case Study of Qiandongnan, China

Min Wang, Qianxi Zhang, Zhe Cheng, An Huang
1 citations
Land
Land Use and Ecosystem Services
1.11
article

Sustainability Assessment and Spatial Optimization of Minority Characteristic Villages Based on the Minimum Cumulative Resistance Model: A Case Study of Qiandongnan, China

Min Wang, Qianxi Zhang, Zhe Cheng, An Huang
article en
1 citations

Abstract

The sustainable development of minority characteristic villages (MCVs) is crucial to regional diversity, equality, and inclusion. However, it also faces multi-dimensional challenges, especially spatial imbalance. Taking Qiandongnan, China as a typical case, this study employed multiple methods to assess the sustainability of MCVs. First, this study constructed a comprehensive resistance surface integrating social, economic, and environmental dimensions based on the Minimum Cumulative Resistance (MCR) model and conducted a systematic assessment of the sustainability of MCVs in Qiandongnan. Second, this study evaluated the spatial distribution characteristics of MCV’s sustainability based on the kernel density analysis and the gravity model. Finally, this study proposed a targeted spatial optimization pathway. The results reveal there are significant spatial differences in MCVs; villages in the central, southern, and central-western Qiandongnan exhibit stronger sustainability, whereas the southwest and eastern regions are weak. Seven core villages and one key node were identified. Five sustainable development corridors were established to enhance spatial connectivity. This study provides novel insights for optimizing the spatial governance of MCVs for achieving regional sustainable development and enriches the knowledge body of global rural revitalization.

LandVol. 14(6)
Xi'an University of Architecture and Technology (CN), Ningbo University of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 24%
Land Use and Ecosystem Services
1.11
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Sustainability Assessment and Spatial Optimization of Minority Characteristic Villages Based on the Minimum Cumulative Resistance Model: A Case Study of Qiandongnan, China — Min Wang, Qianxi Zhang, et al. · Land (2025) | TGRS Research Map | TGRS