A 30 m annual cropland dataset of China from 1986 to 2021
Beijing Institute of Big Data Research · Tsinghua University · +2 more institutions
Abstract
Abstract. Accurate, detailed, and up-to-date information on cropland extent is crucial for provisioning food security and environmental sustainability. However, because of the complexity of agricultural landscapes and lack of sufficient training samples, it remains challenging to monitor cropland dynamics at high spatial and temporal resolutions across large geographical extents, especially for regions where agricultural land use is changing dramatically. Here we developed a cost-effective annual cropland mapping framework that integrated time-series Landsat satellite imagery, automated training sample generation, as well as machine learning and change detection techniques. We implemented the proposed scheme…
Citation impact
- FWCI
- 45.88
- Percentile
- 100%
- References
- 101
Authors
8Topics & keywords
- Agriculture
- China
- Environmental science
- Physical geography
- Moderate-resolution imaging spectroradiometer
- Sustainability
- Cloud computing
- Food security
- Zero hunger
Funding
- NNNational Natural Science Foundation of ChinaAward: 42090015
- SAScience and Technology Commission of Shanghai MunicipalityAward: 22dz1209602
- SRShenzhen Research Institute, City University of Hong KongAward: SZRI2023-CRF-04
- NKNational Key Research and Development Program of ChinaAwards: 2022YFE0209300, 2022YFB3903703