School of Atmospheric Sciences, Southern Marine Science and Engineering
Guangdong Laboratory (Zhuhai), Sun Yat-sen University, Zhuhai 519082,
Guangdong, China
Jinqing Wang
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
Key Laboratory of Digital Earth Science, Aerospace Information Research
Institute, Chinese Academy of Sciences, Beijing 100094, China
School of Electronic, Electrical and Communication Engineering, University
of Chinese Academy of Sciences, Beijing 100049, China
Jun Mi
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
Key Laboratory of Digital Earth Science, Aerospace Information Research
Institute, Chinese Academy of Sciences, Beijing 100094, China
School of Electronic, Electrical and Communication Engineering, University
of Chinese Academy of Sciences, Beijing 100049, China
Wendi Liu
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
Key Laboratory of Digital Earth Science, Aerospace Information Research
Institute, Chinese Academy of Sciences, Beijing 100094, China
School of Electronic, Electrical and Communication Engineering, University
of Chinese Academy of Sciences, Beijing 100049, China
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10,056
2,858
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13,062
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PDF: 2,858
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Total: 13,062
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EndNote: 205
Views and downloads (calculated since 19 Aug 2022)
Cumulative views and downloads
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Total article views: 11,168 (including HTML, PDF, and XML)
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9,077
1,982
109
11,168
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183
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PDF: 1,982
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BibTeX: 129
EndNote: 183
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Total article views: 1,894 (including HTML, PDF, and XML)
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979
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39
1,894
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Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 13,062 (including HTML, PDF, and XML)
Thereof 12,785 with geography defined
and 277 with unknown origin.
Total article views: 11,168 (including HTML, PDF, and XML)
Thereof 10,940 with geography defined
and 228 with unknown origin.
Total article views: 1,894 (including HTML, PDF, and XML)
Thereof 1,845 with geography defined
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An accurate global 30 m wetland dataset that can simultaneously cover inland and coastal zones is lacking. This study proposes a novel method for wetland mapping and generates the first global 30 m wetland map with a fine classification system (GWL_FCS30), including five inland wetland sub-categories (permanent water, swamp, marsh, flooded flat and saline) and three coastal wetland sub-categories (mangrove, salt marsh and tidal flats).
An accurate global 30 m wetland dataset that can simultaneously cover inland and coastal zones...