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Spatial Coupling Pattern and Driving Forces of Rural Settlements and Arable Land in Alpine Canyon Region of the Maoxian County, China

Author

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  • Lingfan Ju

    (College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China)

  • Huan Yu

    (College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China)

  • Qing Xiang

    (College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China)

  • Wenkai Hu

    (College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China)

  • Xiaoyu Xu

    (School of Earth Systems and Sustainability, Southern Illinois University Carbondale, Carbondale, IL 62901, USA
    Environmental Resources and Policy, Southern Illinois University Carbondale, Carbondale, IL 62901, USA)

Abstract

For mountainous areas in different regions, the study of the spatial coupling relationship between rural settlements and arable land resources is a key aspect of coordinated rural development. In this study, a spatial coupling relationship model and a Geodetector are introduced to explore the spatial coupling relationship and driving factors of rural settlements and arable land in the alpine canyon region. The nearest neighbor index, Voronoi diagram, and landscape pattern index system based on the geographic grid are used to analyze the spatial differentiation characteristics of rural settlements in the alpine canyon region, and the spatial coupling relationship model is introduced to explore the spatial coupling relationship between rural settlements and arable land. Finally, the driving factors of the coupling relationship are detected based on Geodetector. The results show that (1) the spatial distribution of rural settlements in the study area is “T-shaped” with a relatively regular settlement shape; (2) the population in the alpine canyon region is relatively small, and the conflict between people and land is not prominent in most areas, so the overall coupling situation between rural settlements and farming land is dominated by fewer people and more land; and (3) the spatial coupling between rural settlements and arable land in the alpine canyon region is mainly affected by four types of factors: terrain topography, meteorology, soil and population, and economy. The interaction between the factors has a synergistic enhancement effect. The results of the study provide theoretical support for the development of rural settlements in the alpine canyon region.

Suggested Citation

  • Lingfan Ju & Huan Yu & Qing Xiang & Wenkai Hu & Xiaoyu Xu, 2023. "Spatial Coupling Pattern and Driving Forces of Rural Settlements and Arable Land in Alpine Canyon Region of the Maoxian County, China," IJERPH, MDPI, vol. 20(5), pages 1-18, February.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:5:p:4312-:d:1083297
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    References listed on IDEAS

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    1. Elias Rodrigues Cunha & Vitor Matheus Bacani & Elói Panachuki, 2017. "Modeling soil erosion using RUSLE and GIS in a watershed occupied by rural settlement in the Brazilian Cerrado," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(2), pages 851-868, January.
    2. Jules Maurice Habumugisha & Ningsheng Chen & Mahfuzur Rahman & Md Monirul Islam & Hilal Ahmad & Ahmed Elbeltagi & Gitika Sharma & Sharmina Naznin Liza & Ashraf Dewan, 2022. "Landslide Susceptibility Mapping with Deep Learning Algorithms," Sustainability, MDPI, vol. 14(3), pages 1-22, February.
    3. Hao Mei & Jin Yang & Mingshun Xiang & Xiaofeng Yang & Chunjian Wang & Wenheng Li & Suhua Yang, 2022. "Evaluation and Optimization Model of Rural Settlement Habitability in the Upper Reaches of the Minjiang River, China," IJERPH, MDPI, vol. 19(22), pages 1-18, November.
    4. Carmen Carrión-Flores & Elena G. Irwin, 2004. "Determinants of Residential Land-Use Conversion and Sprawl at the Rural-Urban Fringe," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 889-904.
    5. Gao, Chunliu & Cheng, Li, 2020. "Tourism-driven rural spatial restructuring in the metropolitan fringe: An empirical observation," Land Use Policy, Elsevier, vol. 95(C).
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