Global Soil Texture Datasets Optimized from Satellite-Observed Wilting Point

Global Soil Texture Datasets Optimized from Satellite-Observed Wilting Point

This dataset provides global soil texture data optimized by remote sensing estimation of wilting coefficient, with a spatial resolution of 0.25 degree. The dataset incorporates remote sensing-based (e.g., SMAP satellite) estimation of soil wilting point and uses the SCE-UA algorithm to optimize two prevalently used soil texture datasets (i.e., GSDE (Shangguan et al. 2014) and HWSD (Fischer et al., 2008)). Comparison results with in-situ observations (44 stations in North America) show that, the soil moisture and evaporative fraction simulation from the Noah-MP land surface model by using the optimized soil texture have been significantly improved.

File naming and required software

File name:
The optimized soil texture data is provided in NetCDF format, with convention defined as "Optimized scheme - Baseline soil texture data - PedotransferFunction scheme". For example, the name "" refers to the soil texture data optimized by non-organic matter PedotransferFunction based on the GSDE data soil dataset.

Data information reading method:
There are four variables in each NC file: soilcomp is the soil texture data, wth three dimensions (1440*600*n), where n=2 (only sand and clay) or 3 (sand, clay and organic matter) is the number of soil texture components. Lon and lat are longitude and latitude. Since the remote sensing data can have large uncertainty in some areas (such as dense vegetation area, permafrost area, etc.), this data also provides the quality control variable (QC_ Flag). Qc_ Flag=1 indicates that the data has low uncertainty and can be used and analyzed directly; qc_ Flag=nan indicates large data uncertainty, therefore, cautions should be addressed when conducting analysis in these areas.

To read the NC format files, MATLAB and other similar software are recommended. For more information about NetCDF, see

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

He, Q., Lu, H., Zhou, J., Yang, K., Shi, J. (2022). Global Soil Texture Datasets Optimized from Satellite-Observed Wilting Point. National Tibetan Plateau Data Center, DOI: 10.11888/Terre.tpdc.272484. CSTR: 18406.11.Terre.tpdc.272484. (Download the reference: RIS | 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

Copyright & License

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Example of acknowledgement statement is included below: The data set is provided by National Tibetan Plateau Data Center (

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

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Geographic coverage
East: 179.95 West: 179.95
South: 89.95 North: 89.95
  • Temporal resolution: --
  • Spatial resolution: 0.1º - 0.25º
  • File size: 180 MB
  • Views: 416
  • Downloads: 48
  • Access: Open Access
  • Temporal coverage: Static data
  • Updated time: 2022-06-12
: HE Qing    LU Hui   ZHOU Jianhong    YANG Kun   SHI Jiancheng  

Distributor: National Tibetan Plateau Data Center


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