Articles | Volume 16, issue 5
https://doi.org/10.5194/essd-16-2501-2024
https://doi.org/10.5194/essd-16-2501-2024
Data description paper
 | 
29 May 2024
Data description paper |  | 29 May 2024

MODIS daily cloud-gap-filled fractional snow cover dataset of the Asian Water Tower region (2000–2022)

Fangbo Pan, Lingmei Jiang, Gongxue Wang, Jinmei Pan, Jinyu Huang, Cheng Zhang, Huizhen Cui, Jianwei Yang, Zhaojun Zheng, Shengli Wu, and Jiancheng Shi

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Cited articles

Ault, T. W., Czajkowski, K. P., Benko, T., Coss, J., Struble, J., Spongberg, A., Templin, M., and Gross, C.: Validation of the MODIS snow product and cloud mask using student and NWS cooperative station observations in the Lower Great Lakes Region, Remote Sens. Environ., 105, 341–353, https://doi.org/10.1016/j.rse.2006.07.004, 2006. 
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Czyzowska-Wisniewski, E. H., van Leeuwen, W. J. D., Hirschboeck, K. K., Marsh, S. E., and Wisniewski, W. T.: Fractional snow cover estimation in complex alpine-forested environments using an artificial neural network, Remote Sens. Environ., 156, 403–417, https://doi.org/10.1016/j.rse.2014.09.026, 2015. 
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Short summary
It is important to strengthen the continuous monitoring of snow cover as a key indicator of imbalance in the Asian Water Tower (AWT) region. We generate long-term daily gap-free fractional snow cover products over the AWT at 0.005° resolution from 2000 to 2022 based on the multiple-endmember spectral mixture analysis algorithm and the gap-filling algorithm. They can provide highly accurate, quantitative fractional snow cover information for subsequent studies on hydrology and climate.
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