IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v14y2025i3p501-d1602177.html
   My bibliography  Save this article

Analysis of the Spatial Distributions and Mechanisms Influencing Abandoned Farmland Based on High-Resolution Satellite Imagery

Author

Listed:
  • Wei Su

    (School of Tropical Agriculture and Forestry, Hainan University, Haikou 570100, China)

  • Yueming Hu

    (School of Tropical Agriculture and Forestry, Hainan University, Haikou 570100, China
    Guangdong Province Smart Cultivated Land Protection Engineering Technology Research Center, Guangzhou 510545, China)

  • Fangyan Xue

    (School of Tropical Agriculture and Forestry, Hainan University, Haikou 570100, China)

  • Xiaoping Fu

    (School of Information and Communication Engineering, Hainan University, Haikou 570100, China)

  • Hao Yang

    (School of Tropical Agriculture and Forestry, Hainan University, Haikou 570100, China)

  • Hui Dai

    (School of Information and Communication Engineering, Hainan University, Haikou 570100, China)

  • Lu Wang

    (College of International Tourism and Public Administration, Hainan University, Haikou 570100, China)

Abstract

Due to the rapid expansion of urban areas, the aging of agricultural labor, and the loss of rural workforce, some regions in China have experienced farmland abandonment. The use of remote sensing technology allows for the rapid and accurate extraction of abandoned farmland, which is of great significance for research on land-using change, food security protection, and ecological and environmental conservation. This research focuses on Qiaotou Town in Chengmai County, Hainan Province, as the study area. Using four high-resolution satellite imagery scenes, digital elevation models, and other relevant data, the random forest classification method was applied to extract abandoned farmland and analyze its spatial distribution characteristics. The accuracy of the results was verified. Based on these findings, the study examines the influence of four factors—irrigation conditions, slope, accessibility, and proximity to residential areas—on farmland abandonment and proposes corresponding governance policies. The results indicate that the accuracy of abandoned farmland extraction using high-resolution satellite imagery is 93.29%. The phenomenon of seasonal farmland abandonment is more prevalent than perennial farmland abandonment in the study area. Among the influencing factors, the abandonment rate decreases with increasing distance from road buffer zones, increases with greater distance from water systems, and decreases with increasing distance from residential areas. Most of the abandoned farmland is located in areas with gentler slopes, which have a relatively smaller impact on farmland abandonment. This study provides valuable references for the extraction of abandoned farmland and for analyzing the abandonment mechanisms in the study area, which have a profound impact on agricultural economic development and help to support the implementation of rural revitalization strategies.

Suggested Citation

  • Wei Su & Yueming Hu & Fangyan Xue & Xiaoping Fu & Hao Yang & Hui Dai & Lu Wang, 2025. "Analysis of the Spatial Distributions and Mechanisms Influencing Abandoned Farmland Based on High-Resolution Satellite Imagery," Land, MDPI, vol. 14(3), pages 1-20, February.
  • Handle: RePEc:gam:jlands:v:14:y:2025:i:3:p:501-:d:1602177
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/14/3/501/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/14/3/501/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jianzhou Yang & Kai Li & Jianweng Gao & Zhenliang Wang & Jingjing Gong & Shuqi Hu & Qiang Zhang & Zhuang Duan & Yong Li, 2024. "Integrated Assessment and Agricultural Planning in Selenium-Rich Hilly Soils: A Case Study on Land Use, Heavy Metal Contamination, and Nutrient Element Distribution," Land, MDPI, vol. 13(11), pages 1-20, October.
    2. Liang, Xinyuan & Li, Yangbing & Zhou, Yalin, 2020. "Study on the abandonment of sloping farmland in Fengjie County, Three Gorges Reservoir Area, a mountainous area in China," Land Use Policy, Elsevier, vol. 97(C).
    3. Jianchao Guo & Shi Qi & Jiadong Chen & Jinlin Lai, 2024. "Driving Forces behind the Reduction in Cropland Area on Hainan Island, China: Implications for Sustainable Agricultural Development," Land, MDPI, vol. 13(8), pages 1-20, August.
    4. Alcantara, Camilo & Kuemmerle, Tobias & Baumann, Matthias & Bragina, Eugenia V & Griffiths, Patrick & Hostert, Patrick & Knorn, Jan & Müller, Daniel & Prishchepov, Alexander V & Schierhorn, Florian & , 2013. "Mapping the extent of abandoned farmland in Central and Eastern Europe using MODIS time series satellite data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 8(3), pages 1-9.
    5. Müller, Daniel & Leitão, Pedro J. & Sikor, Thomas, 2013. "Comparing the determinants of cropland abandonment in Albania and Romania using boosted regression trees," Agricultural Systems, Elsevier, vol. 117(C), pages 66-77.
    6. Mingjia Yang & Jiabao Luo & Lirong Zhu & Peng Lu, 2024. "Impact of Land Use Change on the Spatiotemporal Evolution of Ecosystem Services in Tropical Islands: A Case Study of Hainan Island, China," Land, MDPI, vol. 13(8), pages 1-18, August.
    7. Shi, Tiechou & Li, Xiubin & Xin, Liangjie & Xu, Xiaohong, 2018. "The spatial distribution of farmland abandonment and its influential factors at the township level: A case study in the mountainous area of China," Land Use Policy, Elsevier, vol. 70(C), pages 510-520.
    8. Ojha, Roshan Babu & Atreya, Kishor & Kristiansen, Paul & Devkota, Deepa & Wilson, Brian, 2022. "A systematic review and gap analysis of drivers, impacts, and restoration options for abandoned croplands in Nepal," Land Use Policy, Elsevier, vol. 120(C).
    Full references (including those not matched with items on IDEAS)

    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. Lu, Dan & Su, Kangchuan & Wang, Zhanpeng & Hou, Mengjie & Li, Xinxin & Lin, Aiwen & Yang, Qingyuan, 2025. "Patterns and drivers of terrace abandonment in China: Monitoring based on multi-source remote sensing data," Land Use Policy, Elsevier, vol. 148(C).
    2. Xu, Dingde & Deng, Xin & Huang, Kai & Liu, Yi & Yong, Zhuolin & Liu, Shaoquan, 2019. "Relationships between labor migration and cropland abandonment in rural China from the perspective of village types," Land Use Policy, Elsevier, vol. 88(C).
    3. Buting Hong & Jicheng Wang & Jiangtao Xiao & Quanzhi Yuan & Ping Ren, 2025. "Spatiotemporal Patterns and Determinants of Cropland Abandonment in Mountainous Regions of China: A Case Study of Sichuan Province," Land, MDPI, vol. 14(3), pages 1-25, March.
    4. Xiaolei Wang & Zihan Zhao & Ximou Han & Jinliang Liu & Jessica Kitch & Yongmei Liu & Hao Yang, 2022. "Evaluating the Evolution of Soil Erosion under Catchment Farmland Abandonment Using Lakeshore Sediment," Sustainability, MDPI, vol. 14(19), pages 1-21, September.
    5. Bo Liu & Wei Song & Qian Sun, 2022. "Status, Trend, and Prospect of Global Farmland Abandonment Research: A Bibliometric Analysis," IJERPH, MDPI, vol. 19(23), pages 1-30, November.
    6. Liang, Xinyuan & Li, Yangbing & Zhou, Yalin, 2020. "Study on the abandonment of sloping farmland in Fengjie County, Three Gorges Reservoir Area, a mountainous area in China," Land Use Policy, Elsevier, vol. 97(C).
    7. Nan Zheng & Le Li & Lijian Han & Xiufang Zhu & Kefei Zhao & Ziyang Zhu & Xiaolan Ye, 2024. "The Relationship between Farmland Abandonment and Urbanization Processes: A Case Study in Four Chinese Urban Agglomerations," Land, MDPI, vol. 13(5), pages 1-22, May.
    8. Subedi, Yuba Raj & Kristiansen, Paul & Cacho, Oscar, 2022. "Reutilising abandoned cropland in the Hill agroecological region of Nepal: Options and farmers’ preferences," Land Use Policy, Elsevier, vol. 117(C).
    9. Yiming Sang & Liangjie Xin, 2023. "Factors Determining Concurrent Reclamation and Abandonment of Cultivated Land on the Qinghai-Tibet Plateau," Land, MDPI, vol. 12(5), pages 1-17, May.
    10. Xuan Luo & Zhaomin Tong & Yifan Xie & Rui An & Zhaochen Yang & Yanfang Liu, 2022. "Land Use Change under Population Migration and Its Implications for Human–Land Relationship," Land, MDPI, vol. 11(6), pages 1-22, June.
    11. Yanwei Wang & Wei Song, 2021. "Mapping Abandoned Cropland Changes in the Hilly and Gully Region of the Loess Plateau in China," Land, MDPI, vol. 10(12), pages 1-16, December.
    12. Yemei Li & Yanfei Shan & Ying Chen, 2021. "Analysis of Farmland Abandonment and Government Supervision Traps in China," IJERPH, MDPI, vol. 18(4), pages 1-27, February.
    13. Chong Jiang & Wei Song, 2021. "Degree of Abandoned Cropland and Socioeconomic Impact Factors in China: Multi-Level Analysis Model Based on the Farmer and District/County Levels," Land, MDPI, vol. 11(1), pages 1-25, December.
    14. Han Li & Wei Song, 2021. "Cropland Abandonment and Influencing Factors in Chongqing, China," Land, MDPI, vol. 10(11), pages 1-21, November.
    15. Shinichi Kitano, 2021. "Estimation of Determinants of Farmland Abandonment and Its Data Problems," Land, MDPI, vol. 10(6), pages 1-17, June.
    16. Xiangdong Wang & Decheng Zhao, 2023. "Study on the Causes of Differences in Cropland Abandonment Levels among Farming Households Based on Hierarchical Linear Model—13,120 Farming Households in 26 Provinces of China as an Example," Land, MDPI, vol. 12(9), pages 1-22, September.
    17. Ziyu Jia & Yan Jiao & Wei Zhang & Zheng Chen, 2022. "Rural Tourism Competitiveness and Development Mode, a Case Study from Chinese Township Scale Using Integrated Multi-Source Data," Sustainability, MDPI, vol. 14(7), pages 1-17, March.
    18. Akpoti, Komlavi & Groen, Thomas & Dossou-Yovo, Elliott & Kabo-bah, Amos T. & Zwart, Sander J., 2022. "Climate change-induced reduction in agricultural land suitability of West-Africa's inland valley landscapes," Agricultural Systems, Elsevier, vol. 200(C).
    19. Yue Zhang & Guihua Liu & Zhixing Ma & Xin Deng & Jiahao Song & Dingde Xu, 2022. "The Influence of Land Attachment on Land Abandonment from the Perspective of Generational Difference: Evidence from Sichuan Province, China," IJERPH, MDPI, vol. 19(18), pages 1-15, September.
    20. Jing Tan & Lei Lin, 2024. "Exploring key social capital indicators for disaster preparedness in rural disaster-prone areas: a boosted regression tree approach," 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. 120(5), pages 4159-4180, March.

    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:jlands:v:14:y:2025:i:3:p:501-:d:1602177. 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.