A global daily soil moisture dataset derived from Chinese FengYun-3B Microwave Radiation Imager (MWRI) (2010-2019)
File name: The soil moisture data is stored in netcdf format, and the file name is“ NNsm-FY-yyyyddd.nc ”, where yyyy stands for year and ddd stands for Julian date. For example, NNsm-FY-2013001.nc represents this document describe the global soil moisture distribution on the first day of 2013.
How to read data: The data is EASE-grid equal-area projection data (with varying latitude and longitude intervals)， rather than usual equal-latitude-longitude data. (for more information about EASE-grid projection, please see https://nsidc.org/data/ease). The NC file of data stores three variables: latitude matrix, longitude matrix and soil moisture matrix, which are latitude (406*1), longitude（964*1） and soil_moisture (406*964) respectively. Projection information is not stored.
A. NC file can be directly read using software such as Matlab. For more information about netcdf, please see http://www.unidata.ucar.edu/software/netcdf.
B. If you want to convert NC file to TIF format, you need a .tif template data with EASE-grid 36km. We provide this data named EASEGrid2_36km.tif, please see the data folder. Here is a tutorial transferring EASE_grid file to TIF, written by a student in our group: https://blog.csdn.net/weixin_38953602/article/details/101158084
Yao, P., Lu, H., Zhao, T., Wu, S., Shi, J. (2021). A global daily soil moisture dataset derived from Chinese FengYun-3B Microwave Radiation Imager (MWRI) (2010-2019). National Tibetan Plateau Data Center, DOI: 10.11888/Terre.tpdc.271954. CSTR: 18406.11.Terre.tpdc.271954. (Download the reference： RIS | Bibtex )Related Literatures:
1. Yao, P.P., Lu, H., Zhao, T.J., Wu, S.L., Shi, J.C., Yang K., Cosh, M.H., Zhang, P. (2022). A global daily soil moisture dataset derived from Chinese FengYun-3B Microwave Radiation Imager (MWRI) (2010-2019) . Scientific Data. (Under Review)( View Details | Bibtex)
2. Yao, P.P., Lu, H., Shi, J.C., Zhao, T.J., Yang K., Cosh, M.H., Gianotti, D.J.S., & Entekhabi, D. (2021). A long term global daily soil moisture dataset derived from AMSR-E and AMSR2 (2002-2019). Scientific Data, 8, 143 (2021). https://doi.org/10.1038/s41597-021-00925-8( View Details | Bibtex)
3. Yao, P.P., Shi, J.C., Zhao, T.J., Lu, H. & Al-Yaari, A. (2017). Rebuilding Long Time Series Global Soil Moisture Products Using the Neural Network Adopting the Microwave Vegetation Index. Remote Sensing 9(1), 35.( View Details | Bibtex)
Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.
National Key Research and development Program (No:2018YFB0504905)
the Second Tibetan Plateau Scientific Expedition and Research Program (STEP) (No:2019QZKK0206)
the Major Research plan of the National Natural Science Foundation of China (No:42090014)
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Example of acknowledgement statement is included below: The data set is provided by National Tibetan Plateau Data Center (http://data.tpdc.ac.cn).
License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)
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