Articles | Volume 14, issue 10
https://doi.org/10.5194/essd-14-4505-2022
https://doi.org/10.5194/essd-14-4505-2022
Data description paper
 | 
12 Oct 2022
Data description paper |  | 12 Oct 2022

GLOBMAP SWF: a global annual surface water cover frequency dataset during 2000–2020

Yang Liu, Ronggao Liu, and Rong Shang

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Cited articles

Al Bitar, A., Parrens, M., Fatras, C., Luque, S. P., and Ieee: Global weekly inland surface water dynamics from L-band microwave, IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Electr Network, 26 September–2 October 2020, WOS:000664335304223, 5089–5092, https://doi.org/10.1109/igarss39084.2020.9324291, 2020. 
Berghuijs, W. R., Woods, R. A., and Hrachowitz, M.: A precipitation shift from snow towards rain leads to a decrease in streamflow, Nat. Clim. Change, 4, 583–586, https://doi.org/10.1038/nclimate2246, 2014. 
Bioresita, F., Puissant, A., Stumpf, A., and Malet, J. P.: A Method for Automatic and Rapid Mapping of Water Surfaces from Sentinel-1 Imagery, Remote Sens., 10, 217, https://doi.org/10.3390/rs10020217, 2018. 
Carroll, M. L., Townshend, J. R. G., DiMiceli, C. M., Loboda, T., and Sohlberg, R. A.: Shrinking lakes of the Arctic: Spatial relationships and trajectory of change, Geophys. Res. Lett., 38, L20406, https://doi.org/10.1029/2011gl049427, 2011. 
Feng, L., Hu, C. M., Chen, X. L., Cai, X. B., Tian, L. Q., and Gan, W. X.: Assessment of inundation changes of Poyang Lake using MODIS observations between 2000 and 2010, Remote Sens. Environ., 121, 80–92, https://doi.org/10.1016/j.rse.2012.01.014, 2012. 
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Short summary
Surface water has been changing significantly with high seasonal variation and abrupt change, making it hard to capture its interannual trend. Here we generated a global annual surface water cover frequency dataset during 2000–2020. The percentage of the time period when a pixel is covered by water in a year was estimated to describe the seasonal dynamics of surface water. This dataset can be used to analyze the interannual variation and change trend of highly dynamic inland water extent.
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