DOI: 10.5281/zenodo.17647384
title: An operational global L-band soil moisture and vegetation optical depth dataset from optimized 40° SMOS brightness temperatures

description: This repository provides daily SMOS-IB brightness temperature (TB), soil moisture (SM), and vegetation optical depth (VOD) products, derived from SMOS observations after reconstructing a noise-reduced 40° mono-angular TB record using the L-MEB radiative transfer model. The optimized 40° TB is consistent with the SMAP viewing geometry and substantially reduces the high-frequency noise present in the CATDS multi-angular SMOS Level-3 TB.

 SMOS-IB SM and VOD were then retrieved using the SMAP-INRAE-BORDEAUX (SMAP-IB) algorithm with updated soil roughness map (Li et al., 2022; Konkathi et al., 2025). Evaluations against ISMN soil moisture measurements and multiple vegetation proxies show improved performance compared with multi-angular SMOS products. The dataset provides global daily 40° TB, SM, and VOD at 25 km from 2010 to 2024, suitable for L-band algorithm development and SMAP harmonization, global drought monitoring, and studies of vegetation water and biomass dynamics.

Before doing any application or validation studies, the quality control of the data should be done carefully. For the data filtering, we just need to use Scene_Flags (SF) and RMSE layers.

Firstly, we usually filter the daily SM/VOD values by the conditions “SF <= 1” to remove the strong Topo, frozen scene and polluted scene. Then, we use TB-RMSE <= 8k or TB-RMSE <= 6k to remove strong RFI impact (this RMSE threshold can be higher or lower, but a higher value will reduce the quality of the SM/VOD, and a lower value will mask out too many daily observations; this value depends on your application, usually for global scale validation, we choose 6 or 8K).

Data Format:






Data layer



Description



Units





CRS



Coordinate reference systems (CRS) include spatial reference information and geographic transformation parameters



/





lat



The latitude of the center of each grid cell



degree 





lon



The longitude of the center of each grid cell



degree 





Incidence_Angle



Pixel-based Incidence Angle



degree





TIME_UTC



Year information starting from 2010



/





BT_H



Optimized brightness temperature at H polarization



K





BT_V



Optimized brightness temperature at V polarization



K





Soil_Moisture



Soil Moisture (SM) retrievals



m3/m3





Soil_Moisture_StdError



Error on the derived Soil Moisture



m3/m3





Optical_Thickness_Nad



Vegetation Optical Depth (VOD) retrievals



/





Optical_Thickness_Nad_StdError



Error on the derived Vegetation Optical Depth



/





Soil_Roughness



Global Soil Roughness Map



/





RMSE



Goodness-of-fit between measured TB and modelled TB (Root Mean Square Error, RMSE)



K





Scene_Flags



8-bit flag 

'00000001' : moderate Topography

'00000010' : strong Topography

'00000100' : polluted scene (water+urban+ice > 10% of the pixel),

'00001000' : frozen scene, ECMWF_Surf_Temperature < 273K



/





 

All data are saved in 'netcdf4' format as 64-bit DOUBLE point numbers in NetCDF format on a global EASE Grid (Equal Area Scalable Earth) version 2, with a sampling resolution of 25 km. Each file contains a 584 by 1388 entry map.

Note:

*the normal range of VOD values is [0, 2], and SM is [0,1];

*negative yearly median VOD/SM values, are not physical values and were set equal to zero (mostly distributed in the Sahara Desert and Central Australia);

 

Citation of these papers is compulsory when you use the SMOS-IB product:

Xing et al., 2025. An operational global L-band soil moisture and vegetation optical depth dataset from optimized 40° SMOS brightness temperatures. ESSD. (In submission)

Li, X., Wigneron, J. P., Frappart, F., De Lannoy, G., Fan, L., Zhao, T., ... & Ciais, P. (2022). The first global soil moisture and vegetation optical depth product retrieved from fused SMOS and SMAP L-band observations. Remote Sensing of Environment, 282, 113272.

Li, X., Ciais, P. et al., Large live biomass carbon losses from droughts in the northern temperate ecosystems during 2016-2022. (2025). Nature Communications. https://doi.org/10.1038/s41467-025-59999-2

 

Questions?

Email: xiaojunli_vod@163.com or jean-pierre.wigneron@inrae.fr