Satellite remote sensing provides an efficient pathway to map inland surface water extent across different spatial and temporal scales. However, how to monitor the surface water distribution and its spatiotemporal variability via combining optical and radar remote sensing datasets still faces substantial challenges. A monthyly surface water data set of China derived from optical and radar remote sensing (2018-2020) is provided. The dataset was generated by Seamless Surface Water Mapping Framework (SSWMF) proposed by Yang et al. (2022). The validity of this dataset was further proved over China with an overall accuracy of 92.39% and Kappa coefficient of 0.83. With seamless surface water monitoring, the changes of surface water area can be potentially used to characterize the drought/flood process and evaluate the natural hazard impact.

File naming and required software

Surface water data is stored in TIF format. The name of the file is "chinawateryyy-mm-1. TIF", where yyyy represents year and mm represents month. For example, chinawater2018-7-1.tif represents this TIF file to describe the surface water coverage in China in July 2018.

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Cite as:

Yang, Y. (2021). A monthly surface water dataset of China derived from optical and radar remote sensing (2018-2020). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Hydro.tpdc.271761. CSTR: 18406.11.Hydro.tpdc.271761. (Download the reference： RIS | Bibtex )

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

References literature

1.Yang, Y.M., Huang, S.F., Qiu, J.X., Liu, C.J., & Jiang, W. (2022). A surface water mapping framework combining optical and radar remote sensing and its application in China. Geocarto International, DOI: 10.1080/10106049.2022.2129836 (View Details )

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License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)