IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2023i5p4312-d1083297.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/5/4312/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/20/5/4312/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. Gao, Chunliu & Cheng, Li, 2020. "Tourism-driven rural spatial restructuring in the metropolitan fringe: An empirical observation," Land Use Policy, Elsevier, vol. 95(C).
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lingfan Ju & Yan Liu & Jin Yang & Mingshun Xiang & Qing Xiang & Wenkai Hu & Zhengyi Ding, 2023. "Construction of Nature Reserves’ Ecological Security Pattern Based on Landscape Ecological Risk Assessment: A Case Study of Garze Tibetan Autonomous Prefecture, China," Sustainability, MDPI, vol. 15(11), pages 1-20, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cho, Seong-Hoon & Kim, Heeho & Roberts, Roland K. & Kim, Taeyoung & Lee, Daegoon, 2014. "Effects of changes in forestland ownership on deforestation and urbanization and the resulting effects on greenhouse gas emissions," Journal of Forest Economics, Elsevier, vol. 20(1), pages 93-109.
    2. Lin, Huiyan & Lu, Kang Shou & Espey, Molly & Allen, Jeffery, 2005. "Modeling Urban Sprawl and Land Use Change in a Coastal Area-- A Neural Network Approach," 2005 Annual meeting, July 24-27, Providence, RI 19364, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Changchun Feng & Hao Zhang & Liang Xiao & Yongpei Guo, 2022. "Land Use Change and Its Driving Factors in the Rural–Urban Fringe of Beijing: A Production–Living–Ecological Perspective," Land, MDPI, vol. 11(2), pages 1-18, February.
    4. Carrión-Flores, Carmen E. & Flores-Lagunes, Alfonso & Guci, Ledia, 2018. "An estimator for discrete-choice models with spatial lag dependence using large samples, with an application to land-use conversions," Regional Science and Urban Economics, Elsevier, vol. 69(C), pages 77-93.
    5. Qingqing Yang & Yanhui Gao & Xinjun Yang & Jian Zhang, 2022. "Rural Transformation Driven by Households’ Adaptation to Climate, Policy, Market, and Urbanization: Perspectives from Livelihoods–Land Use on Chinese Loess Plateau," Agriculture, MDPI, vol. 12(8), pages 1-23, July.
    6. Wei Zheng & Hongliang Qiu & Alastair M. Morrison & Wei Wei & Xihua Zhang, 2022. "Landscape and Unique Fascination: A Dual-Case Study on the Antecedents of Tourist Pro-Environmental Behavioral Intentions," Land, MDPI, vol. 11(4), pages 1-20, March.
    7. Barry Kew & Brian D. Lee, 2013. "Measuring Sprawl across the Urban Rural Continuum Using an Amalgamated Sprawl Index," Sustainability, MDPI, vol. 5(5), pages 1-23, April.
    8. Thériault, Marius & Le Berre, Iwan & Dubé, Jean & Maulpoix, Adeline & Vandersmissen, Marie-Hélène, 2020. "The effects of land use planning on housing spread: A case study in the region of Brest, France," Land Use Policy, Elsevier, vol. 92(C).
    9. Suzanne Vallance, 2014. "Living on the Edge: Lessons from the Peri-urban Village," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 38(6), pages 1954-1969, November.
    10. Cuiying Zhou & Jinwu Ouyang & Zhen Liu & Lihai Zhang, 2022. "Early Risk Warning of Highway Soft Rock Slope Group Using Fuzzy-Based Machine Learning," Sustainability, MDPI, vol. 14(6), pages 1-28, March.
    11. Li, Sheng & Nadolnyak, Denis & Hartarska, Valentina, 2019. "Agricultural land conversion: Impacts of economic and natural risk factors in a coastal area," Land Use Policy, Elsevier, vol. 80(C), pages 380-390.
    12. Maples, Chellie H. & Hagerman, Amy D. & Lambert, Dayton M., 2022. "Ex-ante effects of the 2018 Agricultural Improvement Act’s grassland initiative," Land Use Policy, Elsevier, vol. 116(C).
    13. Pengfei Guo & Fangfang Zhang & Haiying Wang & Fen Qin, 2020. "Suitability Evaluation and Layout Optimization of the Spatial Distribution of Rural Residential Areas," Sustainability, MDPI, vol. 12(6), pages 1-15, March.
    14. Martinetti, Davide & Geniaux, Ghislain, 2017. "Approximate likelihood estimation of spatial probit models," Regional Science and Urban Economics, Elsevier, vol. 64(C), pages 30-45.
    15. Lynch, Lori & Geoghegan, Jacqueline, 2011. "FOREWORD: The Economics of Land Use Change: Advancing the Frontiers," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 40(3), pages 1-6, December.
    16. Kathleen P. Bell & Timothy J. Dalton, 2007. "Spatial Economic Analysis in Data‐Rich Environments," Journal of Agricultural Economics, Wiley Blackwell, vol. 58(3), pages 487-501, September.
    17. Ludo Peeters, 2006. "Job Opportunities, Amenities, and Variable Distance-Deterrence Elasticities: An Empirical Model of Inter-Municipal Migration in Belgium," ERSA conference papers ersa06p585, European Regional Science Association.
    18. W. Saart, Patrick & Kim, Namhyun & Bateman, Ian, 2021. "Understanding spatial heterogeneity in GB agricultural land-use for improved policy targeting," Cardiff Economics Working Papers E2021/8, Cardiff University, Cardiff Business School, Economics Section.
    19. Raja Chakir & Olivier Parent, 2009. "Determinants of land use changes: A spatial multinomial probit approach," Papers in Regional Science, Wiley Blackwell, vol. 88(2), pages 327-344, June.
    20. Carmen Carrión-Flores & Elena G. Irwin, 2017. "A fixed effects logit model of rural land conversion and zoning," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 58(1), pages 181-208, January.

    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:jijerp:v:20:y:2023:i:5:p:4312-:d:1083297. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.