A 10-meter resolution dataset of abandoned and reclaimed cropland from 2016 to 2023 in Inner Mongolia, China
文献类型： 外文期刊
作者： Wuyun, Deji 1 ; Sun, Liang 1 ; Chen, Zhongxin 2 ; Li, Yangwei 1 ; Han, Mengwei 1 ; Shi, Zhenxin 1 ; Ren, Tingting 3 ; Zhao, Hongwei 1 ;
作者机构： 1.Chinese Acad Agr Sci, State Key Lab Efficient Utilizat Arable Land China, Beijing, Peoples R China
2.Food & Agr Org United Nations, Digitizat & Informat Div, Rome, Italy
3.Nanjing Agr Univ, Asia Hub, Nanjing 210095, Peoples R China
4.Inst Rural Econ & Informat, Inner Mongolia Acad Agr & Anim Husb Sci, Hohhot 010030, Peoples R China
期刊名称：SCIENTIFIC DATA （ 影响因子：6.9； 五年影响因子：8.7 ）
ISSN：
年卷期： 2025 年 12 卷 1 期
页码：
收录情况： SCI
摘要： Amid growing global food security concerns and frequent armed conflicts, real-time monitoring of abandoned cropland is essential for strategic planning and crisis management. This study develops a method to map abandoned cropland accurately, crucial for maintaining the food supply chain and ecological balance. Utilizing Sentinel-1/2 satellite data, we employed multi-feature stacking and machine learning to create the ARCC10-IM (Abandoned and Reclaimed Cropland Classification at 10-meter resolution in Inner Mongolia) dataset, which tracks annual cropland activity. A novel temporal segmentation algorithm was developed to extract cropland abandonment and reclamation patterns annually, using sliding time windows over several years. This research differentiates cropland states-active cultivation, unstable fallowing, continuous abandonment, and reclamation-providing continuous, regional-scale maps with 10-meter resolution. ARCC10-IM is crucial for land planning, environmental monitoring, and agricultural management in arid areas like Inner Mongolia, enhancing decision-making and technology in land use tracking.
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