A long term global daily soil moisture dataset derived from AMSR-E and AMSR2 (2002-2019)

This dataset contains 18 years (2002-2019) global spatio-temporal consistent surface soil moisture . The resolution is 36 km at daily scale, and the data unit is m3 / m3. This dataset adopts the soil moisture neural network retrieval algorithm developed by Yao et al. (2017). This study transfers the merits of SMAP to AMSR-E/2 through using an Artificial Neural Network (ANN) in which SMAP standard SSM products serve as training targets with AMSR-E/2 brightness temperature (TB) as input. Finally, long term soil moisture data are output. The accuracy is about 5% volumetric water content. (evaluation accuracy of 14 dense ground network globally.)

File naming and required software

File name: the soil moisture data is stored in netcdf format, and the file name is“ yyyyddd.nc ”, where yyyy stands for year and ddd stands for Julian date. For example, 2003001.nc represents this document describe the global soil moisture distribution on the first day of 2003.
How to read data: for more information about netcdf, please see http://www.unidata.ucar.edu/software/netcdf.

Data Citations Data citation guideline What's data citation?
Cite as:

YAO Panpan, LU Hui. A long term global daily soil moisture dataset derived from AMSR-E and AMSR2 (2002-2019). National Tibetan Plateau Data Center, 2020. DOI: 10.11888/Soil.tpdc.270960. (Download the reference: RIS | Bibtex )

Related Literatures:

1. 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)

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. (Accepted)( 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

Second Tibetan Plateau Scientific Expedition Program

the National Key Research and Development Program of China (No:2017YFA0603703)

the Strategic Priority Research Program of Chinese Academy of Sciences (No:XDA20100103)

Copyright & License

To respect the intellectual property rights, protect the rights of data authors,expand servglacials of the data center, and evaluate the application potential of data, data users should clearly indicate the source of the data and the author of the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results). For re-posting (second or multiple releases) data, the author must also indicate the source of the original data.

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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Geographic coverage
East: 179.82 West: -179.82
South: -83.64 North: 83.64
  • Temporal resolution: Daily
  • Spatial resolution: 10km - 100km
  • File size: 19,251 MB
  • Views: 1,473
  • Downloads: 130
  • Access: Open Access
  • Temporal coverage: 2002-07-27 To 2020-02-25
  • Updated time: 2020-12-02
: YAO Panpan   LU Hui  

Distributor: National Tibetan Plateau Data Center

Email: data@itpcas.ac.cn

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