A fine-resolution soil moisture dataset for China in 2002~2018
Authors/Creators
- 1. School of Physics and Electronic-Engineerring, Ningxia University; School of Earth Sciences and Engineering, Hohai University
- 2. School of Physics and Electronic-Engineerring, Ningxia University; Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences
- 3. School of Surveying and Geo-Informatics, Shandong Jianzhu University
- 4. National Space Science Center, Chinese Academy of Sciences; State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Aerospace Information Research Institute of Chinese Academy of Sciences and Beijing Normal University
- 5. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Aerospace Information Research Institute of Chinese Academy of Sciences and Beijing Normal University
- 6. Civil and Environmental Engineering, University of Connecticut
- 7. School of Earth and Space Sciences, Peking University
- 8. School of Physics and Electronic-Engineerring, Ningxia University
Description
The SMC dataset present a high spatial resolution monthly soil moisture raster dataset over China, spanning form the year 2002 to 2018, and the data are presented over a grid with 0.05°. The data set consists of satellite-based AMSR-E/2 and SMOS SM, and base on a spatially weighted decomposition (SWD) model, using the TVDI calculated from MODIS LST/NDVI data as a weighting factor, downscaling to obtain fine spatial resolution SM. Overall, new datasets were strongly correlated with in-situ observations (correlation coefficient R: 0.82, 0.88, and 0.9 and unbiased root mean square error (ubRMSE): 0.051, 0.048 and 0.042 m3m-3 on monthly, seasonal and annual scales, respectively). The dataset unprecedentedly long-term high spatial resolution offers important advantages for drought monitoring and its assessment at district and river basin level climate change in China.
Files
Files
(221.4 MB)
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md5:f166c2af9bc75c80d0787e3c51386b44
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md5:84a14b297c96a063e32ea9b356450a25
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221.4 MB | Download |