Articles | Volume 15, issue 1
https://doi.org/10.5194/essd-15-265-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-265-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
GWL_FCS30: a global 30 m wetland map with a fine classification system using multi-sourced and time-series remote sensing imagery in 2020
Xiao Zhang
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
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
Tingting Zhao
International Research Center of Big Data for Sustainable Development
Goals, Beijing 100094, China
College of Geomatics, Xi'an University of Science and Technology, Xi'an
710054, China
Xidong Chen
North China University of Water Resources and Electric Power, Zhengzhou
450046, China
Shangrong Lin
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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Latest update: 23 Nov 2024
Short summary
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...
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