Articles | Volume 18, issue 6
https://doi.org/10.5194/essd-18-4047-2026
https://doi.org/10.5194/essd-18-4047-2026
Data description article
 | 
15 Jun 2026
Data description article |  | 15 Jun 2026

An operational global L-band soil moisture and vegetation optical depth dataset from optimized 40° SMOS brightness temperatures for 2010–2024

Zanpin Xing, Xiaojun Li, Frédéric Frappart, Gabrielle De Lannoy, Thomas Jagdhuber, Jian Peng, Lei Fan, Hongliang Ma, Lanka Karthikeyan, Xiangzhuo Liu, Mengjia Wang, Lin Zhao, Yongqin Liu, and Jean-Pierre Wigneron

Related authors

Brief communication: delivering a Digital-Twin-ready snow reanalysis
Francesco Avanzi, Hans Lievens, Michael Matiu, Paolo Filippucci, Oscar M. Baez Villanueva, Simone Gabellani, Fabio Delogu, Lorenzo Alfieri, Andrea Libertino, Pere Quintana-Seguì, Diego G. Miralles, Luca Brocca, Christian Massari, and Gabriëlle J. M. De Lannoy
EGUsphere, https://doi.org/10.5194/egusphere-2026-2851,https://doi.org/10.5194/egusphere-2026-2851, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
From sub-daily to multi-year: permafrost ground surface deformation processes revealed by collocated multi-sensor observations at a supersite on the Tibetan Plateau
Lingxiao Wang, Wei Wan, Lin Zhao, Wei Chen, Chong Wang, Shibo Liu, Guangyue Liu, Yuanwei Wang, Junhao Qu, Defu Zou, Erji Du, Guojie Hu, Yao Xiao, Yonghua Zhao, and Minxuan Xiao
EGUsphere, https://doi.org/10.5194/egusphere-2026-2170,https://doi.org/10.5194/egusphere-2026-2170, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Machine learning for snow depth estimation over the European Alps, using Sentinel-1 observations, meteorological forcing data and process-based model simulations
Lucas Boeykens, Devon Dunmire, Jonas-Frederik Jans, Willem Waegeman, Gabriëlle De Lannoy, Ezra Beernaert, Niko E. C. Verhoest, and Hans Lievens
The Cryosphere, 20, 3187–3216, https://doi.org/10.5194/tc-20-3187-2026,https://doi.org/10.5194/tc-20-3187-2026, 2026
Short summary
A pan-tropical 5-km monthly L-band vegetation optical depth dataset from pan-sharpening-based downscaling
Jinan Shi, Jiaxin Li, Lianru Gao, Siyu Liu, Rasmus Fensholt, Philippe Ciais, Xiaojun Li, Qiangqiang Yuan, Jean-Pierre Wigneron, and Lei Fan
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-193,https://doi.org/10.5194/essd-2026-193, 2026
Preprint under review for ESSD
Short summary
On the gap between crop and land surface models: comparing irrigation and other land surface estimates from AquaCrop and Noah-MP over the Po Valley
Louise Busschaert, Michel Bechtold, Sara Modanesi, Christian Massari, Dirk Raes, Sujay V. Kumar, and Gabriëlle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 30, 2579–2611, https://doi.org/10.5194/hess-30-2579-2026,https://doi.org/10.5194/hess-30-2579-2026, 2026
Short summary

Cited articles

Al Bitar, A., Mialon, A., Kerr, Y. H., Cabot, F., Richaume, P., Jacquette, E., Quesney, A., Mahmoodi, A., Tarot, S., Parrens, M., Al-Yaari, A., Pellarin, T., Rodriguez-Fernandez, N., and Wigneron, J.-P.: The global SMOS Level 3 daily soil moisture and brightness temperature maps, Earth Syst. Sci. Data, 9, 293–315, https://doi.org/10.5194/essd-9-293-2017, 2017. 
Al-Yaari, A., Wigneron, J. P., Dorigo, W., Colliander, A., Pellarin, T., Hahn, S., Mialon, A., Richaume, P., Fernandez-Moran, R., Fan, L., Kerr, Y. H., and De Lannoy, G.: Assessment and inter-comparison of recently developed/reprocessed microwave satellite soil moisture products using ISMN ground-based measurements, Remote Sens. Environ., 224, 289–303, https://doi.org/10.1016/j.rse.2019.02.008, 2019. 
Baur, M. J., Friend, A. D., and Pellegrini, A. F. A.: Widespread and systematic effects of fire on plant–soil water relations, Nat. Geosci., 17, 1115–1120, https://doi.org/10.1038/s41561-024-01563-6, 2024. 
Download
Short summary
Microwave satellite observations of Earth’s land surface are important for tracking global soil moisture and vegetation water content. We use data from the Soil Moisture and Ocean Salinity satellite to first reduce noise and contamination in microwave signals, then produce more reliable long-term records of these variables. Tests against ground stations and other satellites show that the new record performs better than existing products and supports drought, freeze-thaw, and carbon monitoring.
Share
Altmetrics
Final-revised paper
Preprint