The continuous snow cover area in time and space is one of key elements to study of land surface energy and water exhange, mountain hydrology, land surface model, numerical weather forecast and climate change. However, the large number of clouds causes data gaps in the snow cover area from optical remote sensing. The MODIS observations of Terra and aqua, FY-2E and FY-2F VISSR are used to obtain fractional snow cover (subpixel snow cover) which is less affected by the cloud, and the snow cover of the remaining cloud pixels is supplemented according to the time series information. Finally the cloudless daily snow fraction is obtained. This data set includes the daily fractional snow cover at 5 km spatial resolution in the Tibetan Plateau and China.

File naming and required software

File name contains data source (satellite), region name, product level, product name, product date and spatial resolution. For example,"FY2EFandMCD_CHINA_L2_FSC_20121201_5KM.tif". The file is in GeoTIFF format, supported by the commonly used remote sensing softwares ArcGIS, ENVI / IDL and MATLAB.

Data Citations Data citation guideline What's data citation?

Cite as:

Jiang, L. (2019). Cloud-free Fractional Snow Cover from Blended MODIS and FY-2 VISSR. A Big Earth Data Platform for Three Poles, DOI: 10.11888/Snow.tpdc.270958. CSTR: 18406.11.Snow.tpdc.270958. (Download the reference： RIS | Bibtex )

Related Literatures:

1. Wang, G., Jiang, L., Wu, S., Shi, J., Hao, S., & Liu, X. (2017). Fractional Snow Cover Mapping from FY-2 VISSR Imagery of China. Remote Sensing, 9(10), 983.( View Details | Bibtex)

2. Wang, G., Jiang, L., Hao, S., Liu, X., Yang, J., & Cui, H. (2018). Cloud-Free Fractional Snow Cover Estimation from Blended MODIS and FY-2 VISSR Measurements. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 5191-5194).( View Details | Bibtex)

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

Support Program

Satellite observation and simulation studies of the land surface water and energy exchange processes and its effects on global changes (No:2015CB953700)

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