63 citations as recorded by crossref.

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28. Spatiotemporal Variability of Arctic Soil Moisture Detected from High-Resolution RADARSAT-2 SAR Data A. Collingwood et al. 10.1155/2018/5712046
29. On the potential of MetOp ASCAT‐derived soil wetness indices as a new aperture for hydrological monitoring and prediction: a field evaluation over Luxembourg P. Matgen et al. 10.1002/hyp.8316
30. Potential of Sentinel-1 Radar Data for the Assessment of Soil and Cereal Cover Parameters S. Bousbih et al. 10.3390/s17112617
31. Zeroth and First Order Scattering Coefficients Through a Random Rough Air-Soil Interface J. Le Caillec 10.1109/TRS.2023.3321131
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37. Evaluation of the Oh, Dubois and IEM Backscatter Models Using a Large Dataset of SAR Data and Experimental Soil Measurements M. Choker et al. 10.3390/w9010038
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39. Microwave-based vegetation descriptors in the parameterization of water cloud model at L-band for soil moisture retrieval over croplands Z. Wang et al. 10.1080/15481603.2020.1857123
40. A Spatial Distribution Empirical Model of Surface Soil Water Content and Soil Workability on an Unplanted Sugarcane Farm Area Using Sentinel-1A Data towards Precision Agriculture Applications H. Imantho et al. 10.3390/info13100493
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46. Are the Current Expectations for SAR Remote Sensing of Soil Moisture Using Machine Learning Overoptimistic? L. Zhu et al. 10.1109/TGRS.2025.3533927
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52. Change detection approaches for flood extent mapping: How to select the most adequate reference image from online archives? R. Hostache et al. 10.1016/j.jag.2012.05.003
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54. An Air-to-Soil Transition Model for Discrete Scattering-Emission Modelling at L-Band H. Zhao et al. 10.34133/2021/3962350
55. Depth-Resolved Backscatter and Differential Interferometric Radar Imaging of Soil Moisture Profiles: Observations and Models of Subsurface Volume Scattering S. Zwieback et al. 10.1109/JSTARS.2017.2671025
56. Evaluation of IEM, Dubois, and Oh Radar Backscatter Models Using Airborne L-Band SAR R. Panciera et al. 10.1109/TGRS.2013.2286203
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60. On the Retrieval of Soil Moisture in Wheat Fields From L-Band SAR Based on Water Cloud Modeling, the IEM, and Effective Roughness Parameters H. Lievens & N. Verhoest 10.1109/LGRS.2011.2106109
61. Assessing how irrigation practices and soil moisture affect crop growth through monitoring Sentinel-1 and Sentinel-2 data G. Ibrahim et al. 10.1007/s10661-023-11871-w
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