Water-Facing Distribution and Suitability Space for Rural Mountain Settlements Based on Fractal Theory, South-Western China | Land Portal

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Date of publication: 
Febrero 2021
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© 2021 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article.

The establishment of rural settlements in the topographically complex mountainous area of South-Western China is restricted by various geographical features. The fractal characteristics and water-facing distribution of rural mountain settlements and the suitability of spaces for rural mountain settlements were analyzed for a greater scientific understanding of what factors would facilitate a more appropriate selection of residential sites. The results showed that: (1) Rural mountain settlements have significant fractal characteristics—the fractal dimension values of rural mountain settlements in terms of elevation, slope, disaster risk, and water-facing level ranged from 0.853 to 1.071, 0.716 to 0.997, 0.134 to 0.243, and 0.940 to 1.110, respectively. (2) The fractal dimension value of rural mountain settlements initially increased and subsequently decreased with increasing elevation, and gradually decreased with increases in slope and disaster risk, but with wave-curve increases in water-facing levels. (3) The suitable spaces for rural mountain settlements were those with a low disaster risk and with slopes less of than 5° under a water-facing level of 0 ~ 500 m in the elevation range of 1500–2000 m. Currently, 8.77% of rural mountain settlements are situated in high-risk and sub-high-risk areas. The spatial planning of national land in China may enhance the land consolidation of rural mountain settlements and plan for the placement of settlements in suitable spaces while avoiding high-risk areas and sub-high-risk areas to ensure the safety of lives and property. The results from this study could be used as a reference for future revitalization activities and the site selection of rural mountain settlements.

Autores y editores

Author(s), editor(s), contributor(s): 

Yu, Hui
Luo, Yong
Li, Pengshan
Dong, Wei
Yu, Shulin
Gao, Xianghe


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