The SMC dataset contains land soil moisture data for Chinese land spanning from 2002 to 2018, the unit is m3/m3, in monthly temporal and 0.05° spatial resolution. More specifically, it is produced by from three passive microwave remote sensing products: the Japan Aerospace Exploration Agency (JAXA)’s Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and the Advanced Microwave Scanning Radiometer 2 (AMSR2) Level 3 soil moisture data, and SMOS product that was developed by the Institut National de la Recherche Agronomique) (INRA) and Centre d’Etudes Spatiales de la BIOsphère (CESBIO) soil moisture data. To overcome the deficiencies of passive microwave soil moisture products with low resolution, we construct a spatially weighted decomposition (SWD) using TVDI that calculated by Moderate Resolution Imaging Spectroradiometer (MODIS) data, including the land surface temperature (LST) MYD11C3 data and the normalized difference vegetation index (NDVI) MYD13C2 data. Overall, the downscaled soil moisture (SM) products were consistent with the in-situ measurements (R>0.78) and exhibited a low root mean square error (ubRMSE < 0.05 m3/m3), which indicates good accuracy throughout the time series. The dataset can be widely used to significantly improve hydrologic and drought monitoring and can serve as an important input for ecological and other geophysical models.

File naming and required software

There are three versions of data, and the data naming rule in version 3.0 is SM_ YYYY_ MM.tif, where SM represents soil moisture, YYYY represents year and MM represents month.
Data files can be opened and viewed by ArcGIS software.

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Cite as:

Mao, K. (2021). SMC dataset: Soil Moisture in China dataset (2002-2018). A Big Earth Data Platform for Three Poles, DOI: 10.5281/zenodo.4738556. (Download the reference： RIS | Bibtex )

Related Literatures:

1. Meng, X., Mao, K., Meng, F., Shi, J., Zeng, J., Shen, X., Cui, Y., Jiang, L., & Guo, Z. (2021). A fine-resolution soil moisture dataset for China in 2002–2018. Earth System Science Data, 13(7), 3239–3261. https://doi.org/10.5194/essd-13-3239-2021( View Details | Bibtex)

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

Copyright & License

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