44 citations as recorded by crossref.

1. Error Propagation in Microwave Soil Moisture and Vegetation Optical Depth Retrievals A. Feldman et al. https://doi.org/10.1109/JSTARS.2021.3124857
2. Spatial-temporal variability pattern of multi-depth soil moisture jointly driven by climatic and human factors in China Y. Liu & Y. Yang https://doi.org/10.1016/j.jhydrol.2023.129313
3. Evaluation of SMAP Core Validation Site Representativeness Errors Using Dense Networks of In Situ Sensors and Random Forests J. Whitcomb et al. https://doi.org/10.1109/JSTARS.2020.3033591
4. Improvement of operational airborne gamma radiation snow water equivalent estimates using SMAP soil moisture E. Cho et al. https://doi.org/10.1016/j.rse.2020.111668
5. Bayesian Time Series Approach and Its Application to Retrieve Ground and Vegetation Variables From L-Band Passive Microwave Remote Sensing M. Holmberg et al. https://doi.org/10.1109/TGRS.2025.3585275
6. The Importance of Scale in the Definition of Uncertainties: How do we Best Communicate this to Data Users? C. Bulgin et al. https://doi.org/10.1007/s10712-025-09908-5
7. Evaluating the utility of remotely sensed soil moisture for the characterization of runoff response over Canadian watersheds E. Wadsworth et al. https://doi.org/10.1080/07011784.2019.1691943
8. A new SMAP soil moisture and vegetation optical depth product (SMAP-IB): Algorithm, assessment and inter-comparison X. Li et al. https://doi.org/10.1016/j.rse.2022.112921
9. Bias-Corrected RADARSAT-2 Soil Moisture Dynamics Reveal Discharge Hysteresis at An Agricultural Watershed J. Lee & K. Lindenschmidt https://doi.org/10.3390/rs15102677
10. Accounting for seasonal retrieval errors in the merging of multi-sensor satellite soil moisture products P. Stradiotti et al. https://doi.org/10.1016/j.srs.2025.100242
11. Validation of Remotely Sensed and Modeled Soil Moisture at Forested and Unforested NEON Sites E. Ayres et al. https://doi.org/10.1109/JSTARS.2024.3430928
12. Using spaceborne SAR and ground-based measurements to identify spatial patterns in soil moisture and seasonal thaw timing in permafrost environments of Alaska W. Baxter et al. https://doi.org/10.3389/frsen.2025.1579261
13. Using the Angular Dependence of the Polarization Ratio to Analyze Aircraft Passive Microwave Measurements Over Land R. de Jeu et al. https://doi.org/10.1109/TGRS.2026.3657427
14. A Monte Carlo based adaptive Kalman filtering framework for soil moisture data assimilation A. Gruber et al. https://doi.org/10.1016/j.rse.2019.04.003
15. Forecasting monthly soil moisture at broad spatial scales in sub-Saharan Africa using three time-series models: evidence from four decades of remotely sensed data S. Tesfamichael et al. https://doi.org/10.1080/22797254.2023.2246638
16. Value of microwave soil moisture and thermal-infrared evapotranspiration retrievals for the mapping of irrigation coverage W. Crow et al. https://doi.org/10.1016/j.jag.2025.104773
17. Collection: Datasets From Real-Time In-Situ Soil Monitoring for Agriculture 2025 K. Moore et al. https://doi.org/10.1109/IEEEDATA.2025.3612373
18. Short-Term and Long-Term Surface Soil Moisture Memory Time Scales Are Spatially Anticorrelated at Global Scales K. McColl et al. https://doi.org/10.1175/JHM-D-18-0141.1
19. A global-scale intercomparison of Triple Collocation Analysis- and ground-based soil moisture time-variant errors derived from different rescaling techniques K. Wu et al. https://doi.org/10.1016/j.rse.2022.113387
20. Comparison of high-resolution airborne soil moisture retrievals to SMAP soil moisture during the SMAP validation experiment 2016 (SMAPVEX16) A. Colliander et al. https://doi.org/10.1016/j.rse.2019.04.004
21. Satellite detection of varying seasonal water supply restrictions on grassland productivity in the Missouri basin, USA G. A et al. https://doi.org/10.1016/j.rse.2019.111623
22. A review of forward modelling and retrieval approaches for forest soil moisture and vegetation optical depth using L-band radiometry A. Colliander et al. https://doi.org/10.1016/j.rse.2025.115158
23. Enhanced L-MEB Model for Soil Moisture Retrieval Over Soybean Fields During the Growing Season K. Cui et al. https://doi.org/10.1109/TGRS.2025.3564927
24. Time-variant error characterization of SMAP and ASCAT soil moisture using Triple Collocation Analysis K. Wu et al. https://doi.org/10.1016/j.rse.2021.112324
25. Investigating multiple causes of time-varying SMAP soil moisture biases based on core validation sites data X. Fan et al. https://doi.org/10.1016/j.jhydrol.2022.128151
26. Land surface modeling over the Dry Chaco: the impact of model structures, and soil, vegetation and land cover parameters M. Maertens et al. https://doi.org/10.5194/hess-25-4099-2021
27. Validation practices for satellite soil moisture retrievals: What are (the) errors? A. Gruber et al. https://doi.org/10.1016/j.rse.2020.111806
28. Vegetation signal crosstalk present in official SMAP surface soil moisture retrievals W. Crow & A. Feldman https://doi.org/10.1016/j.rse.2024.114466
29. Soil Salinity Dynamics Impairs Radiometer-Based Soil Moisture Retrieval Over Global Cropland X. Fan et al. https://doi.org/10.1109/TGRS.2022.3181586
30. Assessing the Spatial Similarity of Soil Moisture Patterns and Their Environmental and Observational Drivers from Remote Sensing and Earth System Modeling Across Europe T. Jagdhuber et al. https://doi.org/10.3390/rs18040608
31. 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
32. Clarifications on the equations and the sample number in triple collocation analysis using SST observations C. Tsamalis https://doi.org/10.1016/j.rse.2022.112936
33. Assessing global passive microwave soil moisture retrievals in mountainous terrain: insights from in situ validation and extended triple collocation Y. Yang et al. https://doi.org/10.1016/j.geoderma.2026.117707
34. Improving Permafrost Modeling by Assimilating Remotely Sensed Soil Moisture S. Zwieback et al. https://doi.org/10.1029/2018WR023247
35. Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology A. Gruber et al. https://doi.org/10.5194/essd-11-717-2019
36. Vegetation–soil moisture coupling metrics from dual-polarization microwave radiometry using regularization S. Zwieback et al. https://doi.org/10.1016/j.rse.2019.111257
37. Analyzing Effects of Crops on SMAP Satellite-Based Soil Moisture Using a Rainfall–Runoff Model in the U.S. Corn Belt N. Jadidoleslam et al. https://doi.org/10.1109/JSTARS.2021.3131133
38. Comprehensive assessment of Fengyun-3 satellites derived soil moisture with in-situ measurements across the globe Y. Liu et al. https://doi.org/10.1016/j.jhydrol.2020.125949
39. SMAP underestimates soil moisture in vegetation-disturbed areas primarily as a result of biased surface temperature data X. Fan et al. https://doi.org/10.1016/j.rse.2020.111914
40. Parameterization of Vegetation Scattering Albedo in the Tau-Omega Model for Soil Moisture Retrieval on Croplands C. Park et al. https://doi.org/10.3390/rs12182939
41. L-band remote-sensing increases sampled levels of global soil moisture-air temperature coupling strength J. Dong & W. Crow https://doi.org/10.1016/j.rse.2018.10.024
42. Validation of Soil Moisture Data Products From the NASA SMAP Mission A. Colliander et al. https://doi.org/10.1109/JSTARS.2021.3124743
43. Impact of vegetation water content information on soil moisture retrievals in agricultural regions: An analysis based on the SMAPVEX16-MicroWEX dataset J. Judge et al. https://doi.org/10.1016/j.rse.2021.112623
44. Assessment of five SMAP soil moisture products using ISMN ground-based measurements over varied environmental conditions C. Yi et al. https://doi.org/10.1016/j.jhydrol.2023.129325