GWL_FCS30: a global 30&thinsp;m wetland map with a fine classification system using multi-sourced and time-series remote sensing imagery in 2020

Zhang, Xiao; Liu, Liangyun; Zhao, Tingting; Chen, Xidong; Lin, Shangrong; Wang, Jinqing; Mi, Jun; Liu, Wendi

doi:https://doi.org/10.5194/essd-15-265-2023

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.

https://doi.org/10.5194/essd-15-265-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 1

Data description paper

|

17 Jan 2023

Data description paper |

| 17 Jan 2023

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, Liangyun Liu, Tingting Zhao, Xidong Chen, Shangrong Lin, Jinqing Wang, Jun Mi, and Wendi Liu

Data sets

GWL_FCS30: global 30 m wetland map with fine classification system using multi-sourced and time-series remote sensing imagery in 2020 Liangyun Liu, Xiao Zhang, and Tingting Zhao https://doi.org/10.5281/zenodo.7340516

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).