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Ice Concentration Retrieval from the Analysis of Microwaves: A New Methodology Designed for the Copernicus Imaging Microwave Radiometer.

, , , , , and . Remote. Sens., 12 (7): 1060 (2020)

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Learning Global Evapotranspiration Dataset Corrections from a Water Cycle Closure Supervision., , , and . Remote. Sens., 16 (1): 170 (January 2024)Statistical retrieval of surface and root zone soil moisture using synergy of multi-frequency remotely-sensed observations., , , , and . IGARSS, page 4943-4946. IEEE, (2017)Soil moisture retrieval from SMOS observations using neural networks., , , , , , , , and . IGARSS, page 2431-2434. IEEE, (2014)Monitoring the Temporal Evolution of the Floods in the Lower Mekong Basin using Multisatellite Observations., , , , , , , , , and 3 other author(s). IGARSS, page 5877-5880. IEEE, (2022)Ice Concentration Retrieval from the Analysis of Microwaves: Evaluation of a New Methodology Optimized for the Copernicus Imaging Microwave Radiometer., , , , and . Remote. Sens., 12 (10): 1594 (2020)Sensitivity of satellite observations to snow characteristics., , and . IGARSS, page 2817-2819. IEEE, (2003)Neural Network Uncertainty Assessment Using Bayesian Statistics: A Remote Sensing Application., , and . Neural Comput., 16 (11): 2415-2458 (2004)A Statistical Retrieval of Cloud Parameters for the Millimeter Wave Ice Cloud Imager on Board MetOp-SG., , , and . IEEE Access, (2017)Statistical downscaling of remotely-sensed soil moisture., , , , and . IGARSS, page 2511-2514. IEEE, (2017)Soil Moisture Retrieval Using Neural Networks: Application to SMOS., , , , , , , , , and . IEEE Trans. Geosci. Remote. Sens., 53 (11): 5991-6007 (2015)