School of National Safety and Emergency Management, Beijing Normal
University, Beijing 100875, PR China
Fulu Tao
Key Laboratory of Land Surface Pattern and Simulation, Institute of
Geographical Sciences and Natural Resources Research, Chinese Academy of
Sciences, Beijing 100101, PR China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, PR China
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3,752
1,070
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4,929
367
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134
HTML: 3,752
PDF: 1,070
XML: 107
Total: 4,929
Supplement: 367
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EndNote: 134
Views and downloads (calculated since 29 Aug 2022)
Cumulative views and downloads
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Total article views: 3,855 (including HTML, PDF, and XML)
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3,111
657
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3,855
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125
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PDF: 657
XML: 87
Total: 3,855
Supplement: 248
BibTeX: 86
EndNote: 125
Views and downloads (calculated since 14 Feb 2023)
Cumulative views and downloads
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Total article views: 1,074 (including HTML, PDF, and XML)
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641
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20
1,074
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9
HTML: 641
PDF: 413
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Total: 1,074
Supplement: 119
BibTeX: 11
EndNote: 9
Views and downloads (calculated since 29 Aug 2022)
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Total article views: 4,929 (including HTML, PDF, and XML)
Thereof 4,786 with geography defined
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Total article views: 3,855 (including HTML, PDF, and XML)
Thereof 3,772 with geography defined
and 83 with unknown origin.
Total article views: 1,074 (including HTML, PDF, and XML)
Thereof 1,014 with geography defined
and 60 with unknown origin.
High-spatiotemporal-resolution rice yield datasets are limited over a large region. We proposed an explicit method to predict rice yield based on machine learning methods and generated a seasonal 4 km resolution rice yield dataset across Asia (AsiaRiceYield4km) for 1995–2015. The seasonal rice yield accuracy of AsiaRiceYield4km is high and much improved compared with previous datasets. AsiaRiceYield4km will fill the current data gap and better support agricultural monitoring systems.
High-spatiotemporal-resolution rice yield datasets are limited over a large region. We proposed...
