Spatial Distribution and Land Use of Traditional Villages in Southwest China
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- Li, Feng & Ye, Yaping & Song, Bowen & Wang, Rusong, 2015. "Evaluation of urban suitable ecological land based on the minimum cumulative resistance model: A case study from Changzhou, China," Ecological Modelling, Elsevier, vol. 318(C), pages 194-203.
- Hai-fan Wang & Shang-chia Chiou, 2019. "Research on the Sustainable Development of Traditional Dwellings," Sustainability, MDPI, vol. 11(19), pages 1-14, September.
- Liu, Yansui, 2018. "Introduction to land use and rural sustainability in China," Land Use Policy, Elsevier, vol. 74(C), pages 1-4.
- Xiaodong Xu & Jingping Liu & Ning Xu & Wei Wang & Hui Yang, 2018. "Quantitative Study on the Evolution Trend and Driving Factors of Typical Rural Spatial Morphology in Southern Jiangsu Province, China," Sustainability, MDPI, vol. 10(7), pages 1-20, July.
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Cited by:
- Anqiang Jia & Xiaoxu Liang & Xuan Wen & Xin Yun & Lijian Ren & Yingxia Yun, 2023. "GIS-Based Analysis of the Spatial Distribution and Influencing Factors of Traditional Villages in Hebei Province, China," Sustainability, MDPI, vol. 15(11), pages 1-24, June.
- Liu Jin & Zongqi Wang & Xiaohong Chen, 2022. "Spatial Distribution Characteristics and Influencing Factors of Traditional Villages on the Tibetan Plateau in China," IJERPH, MDPI, vol. 19(20), pages 1-19, October.
- Haoran Su & Yaowu Wang & Zhen Zhang & Wen Dong, 2022. "Characteristics and Influencing Factors of Traditional Village Distribution in China," Land, MDPI, vol. 11(10), pages 1-26, September.
- Shuxin Mao & Hongbing Deng, 2022. "Regional Ecology Supporting Sustainable Development," Sustainability, MDPI, vol. 14(12), pages 1-5, June.
- Xiaogang Feng & Moqing Hu & Sekhar Somenahalli & Xinyuan Bian & Meng Li & Zaihui Zhou & Fengxia Li & Yuan Wang, 2023. "A Study of Spatio-Temporal Differentiation Characteristics and Driving Factors of Shaanxi Province’s Traditional Heritage Villages," Sustainability, MDPI, vol. 15(10), pages 1-18, May.
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Keywords
traditional villages; spatial distribution; influencing factors; landscape pattern; Southwest China;All these keywords.
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