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A Novel Phenology-Based Index for Plastic-Mulched Farmland Extraction and Its Application in a Typical Agricultural Region of China Using Sentinel-2 Imagery and Google Earth Engine

Author

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  • Xinyu Dong

    (College of Surveying and Planning, Shangqiu Normal University, Shangqiu 476000, China
    Henan Engineering Technology Research Center of Ecological Protection and Management of the Old Course of Yellow River, Shangqiu Normal University, Shangqiu 476000, China)

  • Jiaguo Li

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China)

  • Ning Xu

    (College of Surveying and Planning, Shangqiu Normal University, Shangqiu 476000, China
    Henan Engineering Technology Research Center of Ecological Protection and Management of the Old Course of Yellow River, Shangqiu Normal University, Shangqiu 476000, China)

  • Junjie Lei

    (College of Surveying and Planning, Shangqiu Normal University, Shangqiu 476000, China
    Henan Engineering Technology Research Center of Ecological Protection and Management of the Old Course of Yellow River, Shangqiu Normal University, Shangqiu 476000, China)

  • Zhen He

    (College of Surveying and Planning, Shangqiu Normal University, Shangqiu 476000, China
    Henan Engineering Technology Research Center of Ecological Protection and Management of the Old Course of Yellow River, Shangqiu Normal University, Shangqiu 476000, China)

  • Limin Zhao

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China)

Abstract

Plastic-mulching technology has a crucial role to play in modern agriculture by optimizing crop growth environments and enhancing yields. Accurately detecting and mapping the distribution of plastic-mulched farmlands (PMFs) is essential for improving both agricultural management and production efficiency. By analyzing the temporal spectral characteristics of PMFs and crop phenological information, we developed a phenology-based plastic-mulched farmland index (PPMFI). This index, when combined with Sentinel-2 imagery and an automated high-precision extraction process via the Google Earth Engine platform, effectively distinguishes PMFs from other land cover types, especially in complex agricultural landscapes. Validation across areas varying in their background complexity and PMF coverage demonstrated that the proposed PPMFI consistently achieves an overall accuracy rate that exceeds 90%, showcasing its robust performance and significantly outperforming other comparative extraction methods. Applying the PPMFI to the Yudong agricultural region of Henan Province, China, further confirmed its capability for large-scale PMF monitoring, thereby offering critical technical support for sustainable agricultural management and environmental protection.

Suggested Citation

  • Xinyu Dong & Jiaguo Li & Ning Xu & Junjie Lei & Zhen He & Limin Zhao, 2024. "A Novel Phenology-Based Index for Plastic-Mulched Farmland Extraction and Its Application in a Typical Agricultural Region of China Using Sentinel-2 Imagery and Google Earth Engine," Land, MDPI, vol. 13(11), pages 1-23, November.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:11:p:1825-:d:1513070
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    References listed on IDEAS

    as
    1. Zhang, Xucheng & Wang, Hongli & Hou, Huizhi & Yu, Xianfeng & Ma, Yifan & Fang, Yanjie & Lei, Kangning, 2020. "Did plastic mulching constantly increase crop yield but decrease soil water in a semiarid rain-fed area?," Agricultural Water Management, Elsevier, vol. 241(C).
    2. Justas Streimikis & Tomas Baležentis, 2020. "Agricultural sustainability assessment framework integrating sustainable development goals and interlinked priorities of environmental, climate and agriculture policies," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(6), pages 1702-1712, November.
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