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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
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    References listed on IDEAS

    as
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