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Data Details

Snow Cover Dataset by Multi-source Data Fusion Algorithm ─ A Case Study in the Northwestern United States


GAO Yang1DONG Huaiwei1,2
1 Key Laboratory of Tibetan Environment Changes and Land Surface Processes，Institute of Tibetan Plateau Research，Chinese Academy of Sciences，Beijing 100101，China2 College of Geodesy and Geomatics，Shandong University of Science and Technology，Qingdao 266590，China

DOI:10.3974/geodb.2022.02.08.V1

Published:Feb. 2022

Visitors：7000       Data Files Downloaded：21      
Data Downloaded：8850.60 MB      Citations：

Key Words：

snow cover,multisource data,daily data,2000-2020,Northwestern United States,

Abstract：

A comprehensive understanding of the snow cover is of great significance to the measurement of coping with the snow change, the management of regional water resources under continuous warming, and the deeply understanding of global climate change. Based on the latest MODIS NDSI data, IMS snow/ice data and the snow measurements at 192 SNOTEL stations, the authors firstly defined the suitable NDSI threshold for snow recognition according to the snow characteristics in the Northwestern United States, and then formulated various fusion rules based on data performances in different periods. Finally the snow cover dataset by multi-source data fusion algorithm -- a case study in the Northwestern United States was developed. The validation proved that the fusion could improve the accuracy and snow recognition performances compared with the source data. The dataset includes: (1) boundary data of the study area; (2) daily snow cover data in the study area during 2000-2020. In addition, the validation data was attached. The spatial resolution is 500 m. The dataset is archived in .tiff, .shp, .xlsx and .txt data formats, and consists of 7,688 data files with data size of 170 GB (Compressed into one single file with 421 MB).Browse

Foundation Item：

Ministry of Science and Technology of P. R. China (2017YFA0603303); National Natural Science Foundation of China (42171136)

Data Citation：

GAO Yang, DONG Huaiwei. Snow Cover Dataset by Multi-source Data Fusion Algorithm ─ A Case Study in the Northwestern United States[J/DB/OL]. Digital Journal of Global Change Data Repository, 2022. https://doi.org/10.3974/geodb.2022.02.08.V1.

GAO Yang, DONG Huaiwei. Snow cover dataset by multi-source data fusion algorithm—a case study in the Northwestern United States [J]. Journal of Global Change Data & Discovery. 2022, 6(2): 280-289. https://doi.org/10.3974/geodp.2022.02.15.

References：

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Data Product:

ID Data Name Data Size Operation
0Datapaper_SnowCoverTest_2000-2020.pdf1804.00kbDownLoad
1 SnowCoverTest_2000-2020.rar 431572.12KB
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