Articles | Volume 14, issue 7
https://doi.org/10.5194/essd-14-3137-2022
https://doi.org/10.5194/essd-14-3137-2022
Data description paper
 | 
11 Jul 2022
Data description paper |  | 11 Jul 2022

STAR NDSI collection: a cloud-free MODIS NDSI dataset (2001–2020) for China

Yinghong Jing, Xinghua Li, and Huanfeng Shen

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Cited articles

Aalstad, K., Westermann, S., and Bertino, L.: Evaluating satellite retrieved fractional snow-covered area at a high-Arctic site using terrestrial photography, Remote Sens. Environ., 239, 111618, https://doi.org/10.1016/j.rse.2019.111618, 2020. 
Akyurek, Z., Hall, D. K., Riggs, G. A., and Sensoy, A.: Evaluating the utility of the ANSA blended snow cover product in the mountains of eastern Turkey, Int. J. Remote Sens., 31, 3727–3744, https://doi.org/10.1080/01431161.2010.483484, 2010. 
Barnett, T. P., Adam, J. C., and Lettenmaier, D. P.: Potential impacts of a warming climate on water availability in snow-dominated regions, Nature, 438, 303–309, https://doi.org/10.1038/nature04141, 2005. 
Bormann, K. J., Brown, R. D., Derksen, C., and Painter, T. H.: Estimating snow-cover trends from space, Nat. Clim. Change, 8, 923–927, https://doi.org/10.1038/s41558-018-0318-3, 2018. 
Brown, R., Derksen, C., and Wang, L. B.: A multi-data set analysis of variability and change in Arctic spring snow cover extent, 1967–2008, J. Geophys. Res.-Atmos., 115, D16111, https://doi.org/10.1029/2010jd013975, 2010. 
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Short summary
Snow variation is a vital factor in global climate change. Satellite-based approaches are effective for large-scale environmental monitoring. Nevertheless, the high cloud fraction seriously impedes the remote-sensed investigation. Therefore, a recent 20-year cloud-free snow cover collection in China is generated for the first time. This collection can serve as a basic dataset for hydrological and climatic modeling to explore various critical environmental issues.
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