61 citations as recorded by crossref.

1. Estimation of the temporal autocorrelation structure by the collocation technique with an emphasis on soil moisture studies S. Zwieback et al. https://doi.org/10.1080/02626667.2013.839876
2. Testing regression equations to derive long-term global soil moisture datasets from passive microwave observations A. Al-Yaari et al. https://doi.org/10.1016/j.rse.2015.11.022
3. Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite M. Piles et al. https://doi.org/10.3390/rs11010095
4. Estimating sub-daily resolution soil moisture using Fengyun satellite data and machine learning J. Wang et al. https://doi.org/10.1016/j.jhydrol.2024.130814
5. Analysis of SMOS brightness temperature and vegetation optical depth data with coupled land surface and radiative transfer models in Southern Germany F. Schlenz et al. https://doi.org/10.5194/hess-16-3517-2012
6. Monitoring multi-decadal satellite earth observation of soil moisture products through land surface reanalyses C. Albergel et al. https://doi.org/10.1016/j.rse.2013.07.009
7. Assessment and inter-comparison of recently developed/reprocessed microwave satellite soil moisture products using ISMN ground-based measurements A. Al-Yaari et al. https://doi.org/10.1016/j.rse.2019.02.008
8. Validation of Four Satellite-Derived Soil Moisture Products Using Ground-Based In Situ Observations over Northern China W. Liu et al. https://doi.org/10.3390/rs14061419
9. Enhancing hydrological modelling with reanalysis soil moisture: A data-driven approach for optimizing initial conditions through reanalysis integration L. Liu et al. https://doi.org/10.1016/j.advwatres.2025.105023
10. An appraisal of the accuracy of operational soil moisture estimates from SMOS MIRAS using validated in situ observations acquired in a Mediterranean environment G. Petropoulos et al. https://doi.org/10.1080/2150704X.2014.933277
11. Machine Learning–Based Bias Correction of Model-Simulated Soil Moisture Using In-situ AWS Observations Over India H. Fatima et al. https://doi.org/10.1007/s41748-025-00964-w
12. Analysis of ASCAT, SMOS, in-situ and land model soil moisture as a regionalized variable over Europe and North Africa N. Pierdicca et al. https://doi.org/10.1016/j.rse.2015.09.005
13. Assessment of 9 km SMAP soil moisture: Evidence of narrowing the gap between satellite retrievals and model-based reanalysis Z. Xing et al. https://doi.org/10.1016/j.rse.2023.113721
14. A comparison of ASCAT and SMOS soil moisture retrievals over Europe and Northern Africa from 2010 to 2013 F. Fascetti et al. https://doi.org/10.1016/j.jag.2015.09.008
15. Spatial and temporal variability of biophysical variables in southwestern France from airborne L-band radiometry E. Zakharova et al. https://doi.org/10.5194/hess-16-1725-2012
16. Hydrological assessment of atmospheric forcing uncertainty in the Euro-Mediterranean area using a land surface model E. Gelati et al. https://doi.org/10.5194/hess-22-2091-2018
17. Downscaling Satellite Retrieved Soil Moisture Using Regression Tree‐Based Machine Learning Algorithms Over Southwest France Y. Liu et al. https://doi.org/10.1029/2020EA001267
18. Complexity‐reduction modelling for assessing the macro‐scale patterns of historical soil moisture in the Euro‐Mediterranean region N. Diodato et al. https://doi.org/10.1002/hyp.9925
19. Evaluation of the SMOS and SMAP soil moisture products under different vegetation types against two sparse in situ networks over arid mountainous watersheds, Northwest China L. Zhang et al. https://doi.org/10.1007/s11430-018-9308-9
20. Regionalizing Root‐Zone Soil Moisture Estimates From ESA CCI Soil Water Index Using Machine Learning and Information on Soil, Vegetation, and Climate M. Grillakis et al. https://doi.org/10.1029/2020WR029249
21. Comparing surface-soil moisture from the SMOS mission and the ORCHIDEE land-surface model over the Iberian Peninsula J. Polcher et al. https://doi.org/10.1016/j.rse.2015.12.004
22. Automated Quality Control of In Situ Soil Moisture from the North American Soil Moisture Database Using NLDAS-2 Products Y. Xia et al. https://doi.org/10.1175/JAMC-D-14-0275.1
23. Global Scale Mapping of Subsurface Scattering Signals Impacting ASCAT Soil Moisture Retrievals W. Wagner et al. https://doi.org/10.1109/TGRS.2024.3429550
24. State of the Art in Large-Scale Soil Moisture Monitoring T. Ochsner et al. https://doi.org/10.2136/sssaj2013.03.0093
25. Soil Moisture Estimation in Alpine Catchments through Modeling and Satellite Observations L. Brocca et al. https://doi.org/10.2136/vzj2012.0102
26. On the assimilation set-up of ASCAT soil moisture data for improving streamflow catchment simulation J. Loizu et al. https://doi.org/10.1016/j.advwatres.2017.10.034
27. A multi-sourced assessment of the spatiotemporal dynamics of soil moisture in the MARINE flash flood model J. Eeckman et al. https://doi.org/10.5194/hess-25-1425-2021
28. Analysis of two years of ASCAT-and SMOS-derived soil moisture estimates over Europe and North Africa N. Pierdicca et al. https://doi.org/10.5721/EuJRS20134645
29. Comparison of measured brightness temperatures from SMOS with modelled ones from ORCHIDEE and H-TESSEL over the Iberian Peninsula A. Barella-Ortiz et al. https://doi.org/10.5194/hess-21-357-2017
30. Skill and Global Trend Analysis of Soil Moisture from Reanalyses and Microwave Remote Sensing C. Albergel et al. https://doi.org/10.1175/JHM-D-12-0161.1
31. An advanced error correction methodology for merging in-situ observed and model-based soil moisture Z. Wu et al. https://doi.org/10.1016/j.jhydrol.2018.09.018
32. A Multitemporal-Scale Framework for Estimating Subdaily Soil Moisture by Fusing AMSR2 and SMAP Datasets M. Wang et al. https://doi.org/10.1109/TGRS.2026.3703167
33. SMOS soil moisture product evaluation over West-Africa from local to regional scale S. Louvet et al. https://doi.org/10.1016/j.rse.2014.10.005
34. Preliminary validation of two temporal parameter-based soil moisture retrieval models using a satellite product and in situ soil moisture measurements over the REMEDHUS network P. Leng et al. https://doi.org/10.1080/01431161.2016.1253896
35. The International Soil Moisture Network: serving Earth system science for over a decade W. Dorigo et al. https://doi.org/10.5194/hess-25-5749-2021
36. Soil moisture remote-sensing applications for identification of flood-prone areas along transport infrastructure A. Ahlmer et al. https://doi.org/10.1007/s12665-018-7704-z
37. Improving Landslide Forecasting Using ASCAT-Derived Soil Moisture Data: A Case Study of the Torgiovannetto Landslide in Central Italy L. Brocca et al. https://doi.org/10.3390/rs4051232
38. Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model P. Laiolo et al. https://doi.org/10.1016/j.jag.2015.06.002
39. Drought monitoring with soil moisture active passive (SMAP) measurements A. Mishra et al. https://doi.org/10.1016/j.jhydrol.2017.07.033
40. Inter-comparison of SMOS and AMSR-E soil moisture products during flood years (2010–2011) over Pakistan R. Anam et al. https://doi.org/10.1080/22797254.2017.1352461
41. Considering combined or separated roughness and vegetation effects in soil moisture retrievals M. Parrens et al. https://doi.org/10.1016/j.jag.2016.11.001
42. Evaluating soil moisture retrievals from ESA's SMOS and NASA's SMAP brightness temperature datasets A. Al-Yaari et al. https://doi.org/10.1016/j.rse.2017.03.010
43. Evaluation of SMOS, SMAP, ASCAT and Sentinel-1 Soil Moisture Products at Sites in Southwestern France M. El Hajj et al. https://doi.org/10.3390/rs10040569
44. Scale-aware triple collocation: optimizing spatiotemporal windows for enhanced multi-source fusion of meteorological data Z. Peng et al. https://doi.org/10.1016/j.jhydrol.2026.135662
45. A Comparison of ASCAT Soil Moisture Data With <italic>In Situ</italic> Observations Over the Indian Region: A Multiscale Analysis K. Bhimala & P. Goswami https://doi.org/10.1109/TGRS.2015.2422377
46. Comparison of SMOS and SMAP soil moisture retrieval approaches using tower-based radiometer data over a vineyard field M. Miernecki et al. https://doi.org/10.1016/j.rse.2014.08.002
47. Deriving pedotransfer functions for soil quartz fraction in southern France from reverse modeling J. Calvet et al. https://doi.org/10.5194/soil-2-615-2016
48. Application of a Combined Optical–Passive Microwave Method to Retrieve Soil Moisture at Regional Scale Over Chile A. Santamaria-Artigas et al. https://doi.org/10.1109/JSTARS.2015.2512926
49. Remote Sensing of Soil Moisture: An Overview in Relation to Coastal Soils https://doi.org/10.2112/JCOASTRES-D-13-00072.1
50. Uncertainty estimates in the NISAR high-resolution soil moisture retrievals from multi-scale algorithm P. Lal et al. https://doi.org/10.1016/j.rse.2024.114288
51. An assessment of remotely sensed surface and root zone soil moisture through active and passive sensors in northeast Asia E. Cho et al. https://doi.org/10.1016/j.rse.2015.01.013
52. Quality Control and Evaluation of the Observed Daily Data in the North American Soil Moisture Database W. Liao et al. https://doi.org/10.1007/s13351-019-8121-2
53. Impact of ASCAT Soil Moisture Assimilation on Regional Precipitation Forecasts: A Case Study for Austria S. Schneider et al. https://doi.org/10.1175/MWR-D-12-00311.1
54. Global Automated Quality Control of In Situ Soil Moisture Data from the International Soil Moisture Network W. Dorigo et al. https://doi.org/10.2136/vzj2012.0097
55. Global-scale assessment and combination of SMAP with ASCAT (active) and AMSR2 (passive) soil moisture products H. Kim et al. https://doi.org/10.1016/j.rse.2017.10.026
56. Evidence of a topographic signal in surface soil moisture derived from ENVISAT ASAR wide swath data D. Mason et al. https://doi.org/10.1016/j.jag.2015.02.004
57. Global-scale comparison of passive (SMOS) and active (ASCAT) satellite based microwave soil moisture retrievals with soil moisture simulations (MERRA-Land) A. Al-Yaari et al. https://doi.org/10.1016/j.rse.2014.07.013
58. Estimation of antecedent wetness conditions for flood modelling in northern Morocco Y. Tramblay et al. https://doi.org/10.5194/hess-16-4375-2012
59. A triple collocation-based 2D soil moisture merging methodology considering spatial and temporal non-stationary errors J. Zhou et al. https://doi.org/10.1016/j.rse.2021.112509
60. Operational Soil Moisture from ASCAT in Support of Water Resources Management K. Deng et al. https://doi.org/10.3390/rs11050579
61. Quantifying the potential of using Soil Moisture Active Passive (SMAP) soil moisture variability to predict subsurface water dynamics A. Nayak et al. https://doi.org/10.5194/hess-29-215-2025