Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of
Agriculture and Rural Affairs/Institute of Agricultural Resources and
Regional Planning, Chinese Academy of Agricultural Sciences, Beijing,
100081, China
Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of
Agriculture and Rural Affairs/Institute of Agricultural Resources and
Regional Planning, Chinese Academy of Agricultural Sciences, Beijing,
100081, China
Liangzhi You
Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of
Agriculture and Rural Affairs/Institute of Agricultural Resources and
Regional Planning, Chinese Academy of Agricultural Sciences, Beijing,
100081, China
International Food Policy Research Institute (IFPRI), Washington, DC,
20005-3915, USA
International Institute for Applied Systems Analysis, ESM, Laxenburg,
2361, Austria
Qiangyi Yu
Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of
Agriculture and Rural Affairs/Institute of Agricultural Resources and
Regional Planning, Chinese Academy of Agricultural Sciences, Beijing,
100081, China
Yanbing Wei
Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of
Agriculture and Rural Affairs/Institute of Agricultural Resources and
Regional Planning, Chinese Academy of Agricultural Sciences, Beijing,
100081, China
Di Chen
Institute of Environment and Sustainable Development in Agriculture,
Chinese Academy of Agricultural Sciences, Beijing, 100081, China
Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of
Agriculture and Rural Affairs/Institute of Agricultural Resources and
Regional Planning, Chinese Academy of Agricultural Sciences, Beijing,
100081, China
Bing Xue
School of Engineering and Computer Science, Victoria University of
Wellington, Wellington, 6140, New Zealand
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192
255
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PDF: 1,689
XML: 166
Total: 7,713
BibTeX: 192
EndNote: 255
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Cumulative views and downloads
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Total article views: 6,794 (including HTML, PDF, and XML)
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5,389
1,289
116
6,794
146
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HTML: 5,389
PDF: 1,289
XML: 116
Total: 6,794
BibTeX: 146
EndNote: 209
Views and downloads (calculated since 28 Aug 2020)
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469
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Viewed (geographical distribution)
Total article views: 7,713 (including HTML, PDF, and XML)
Thereof 6,959 with geography defined
and 754 with unknown origin.
Total article views: 6,794 (including HTML, PDF, and XML)
Thereof 6,130 with geography defined
and 664 with unknown origin.
Total article views: 919 (including HTML, PDF, and XML)
Thereof 829 with geography defined
and 90 with unknown origin.
Global cropland distribution is critical for agricultural monitoring and food security. We propose a new Self-adapting Statistics Allocation Model (SASAM) to develop the global map of cropland distribution. SASAM is based on the fusion of multiple existing cropland maps and multilevel statistics of cropland area, which is independent of training samples. The synergy map has higher accuracy than the input datasets and better consistency with the cropland statistics.
Global cropland distribution is critical for agricultural monitoring and food security. We...
