Author
Listed:
- Zhiqiang Gan
(Anhui Institute of Territorial Space Planning and Ecology, Hefei 230009, China
School of Forestry and Landscape Architecture, Anhui Agricultural University, Hefei 230036, China
Low Carbon Urban-Rural Planning and Design Innovation Research Institute, Anhui Agricultural University, Hefei 230036, China)
- Jingyuan Chen
(School of Forestry and Landscape Architecture, Anhui Agricultural University, Hefei 230036, China
Low Carbon Urban-Rural Planning and Design Innovation Research Institute, Anhui Agricultural University, Hefei 230036, China)
- Yefeng Li
(School of Forestry and Landscape Architecture, Anhui Agricultural University, Hefei 230036, China
Low Carbon Urban-Rural Planning and Design Innovation Research Institute, Anhui Agricultural University, Hefei 230036, China)
- Yunbin Zhang
(School of Forestry and Landscape Architecture, Anhui Agricultural University, Hefei 230036, China
Low Carbon Urban-Rural Planning and Design Innovation Research Institute, Anhui Agricultural University, Hefei 230036, China)
- Meng Zhu
(School of Forestry and Landscape Architecture, Anhui Agricultural University, Hefei 230036, China
Low Carbon Urban-Rural Planning and Design Innovation Research Institute, Anhui Agricultural University, Hefei 230036, China)
- Dan Li
(Anhui Institute of Territorial Space Planning and Ecology, Hefei 230009, China
School of Forestry and Landscape Architecture, Anhui Agricultural University, Hefei 230036, China
Low Carbon Urban-Rural Planning and Design Innovation Research Institute, Anhui Agricultural University, Hefei 230036, China)
Abstract
Examining the spatial differentiation and constraining factors of rural resilience at the micro-scale is essential for navigating compounded risks and unbalanced urban–rural development. The study takes 170 villages in Qianshan City, Anhui Province, as the study sample and constructs a four-dimensional resilience evaluation system encompassing economic, social, infrastructural, and ecological dimensions. The research systematically assesses rural resilience levels and obstacle factors using the entropy weight method, spatial autocorrelation analysis, and the obstacle degree model. The results indicate that: (1) The overall rural comprehensive resilience in Qianshan City is at a moderately low level, with an average value of 0.133, ranging from 0.0604 to 0.4805. Significant inter-village disparities exist, forming a distinct “central agglomeration–peripheral dispersion” spatial pattern driven by urban proximity. (2) The resilience of each subsystem also exhibits pronounced heterogeneity: economic resilience is generally low; infrastructural resilience shows the greatest variation; social resilience is relatively stable in its spatial distribution; and ecological resilience demonstrates a “high in the northwest–low in the southeast” pattern. (3) Hotspots of comprehensive resilience, as well as economic, social, and infrastructural resilience, are concentrated around the central–southern urban areas with stronger development foundations, whereas hotspots of ecological resilience are independently distributed within ecologically advantageous zones. (4) Rural resilience is primarily constrained by deficits in public service accessibility and infrastructure conditions. Notably, the primary obstacle factors exhibit high consistency across villages with different geomorphic conditions. Finally, this study proposes coordinated enhancement strategies for economic development, infrastructure improvement, ecological conservation, and social governance in Qianshan City, providing a scientific basis for rural resilience building and governance.
Suggested Citation
Zhiqiang Gan & Jingyuan Chen & Yefeng Li & Yunbin Zhang & Meng Zhu & Dan Li, 2026.
"Spatial Differentiation and Obstacle Factors of Rural Resilience at the Village Scale: Empirical Evidence from Qianshan City, Anhui Province, China,"
Sustainability, MDPI, vol. 18(5), pages 1-26, March.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:5:p:2440-:d:1876733
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:18:y:2026:i:5:p:2440-:d:1876733. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.