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Utilizing complementarity of active/passive microwave observations at L-band for soil moisture studies in sandy soils., , , , and . IGARSS, page 743-746. IEEE, (2013)Comparison of Backscattering Models at L-Band for Growing Corn., and . IEEE Geosci. Remote. Sens. Lett., 8 (1): 24-28 (2011)Assimilation of Active and Passive Microwave Observations for Improved Estimates of Soil Moisture and Crop Growth., , , , , , and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 9 (4): 1357-1369 (2016)Microwave Backscatter Phenomenology of Corn Fields at L-Band Using a Full-Wave Electromagnetic Solver., , , , , and . IEEE Trans. Geosci. Remote. Sens., (2024)Domain-guided Machine Learning for Remotely Sensed In-Season Crop Growth Estimation., , and . CoRR, (2021)Remotely sensed vegetation index and LAI for parameter determination of the CSM-CROPGRO-Soybean model when in situ data are not available., , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2019)Towards Understanding the Influence of Vertical Water Distribution on Radar Backscatter from Vegetation Using a Multi-Layer Water Cloud Model., , , , and . Remote. Sens., 14 (16): 3867 (2022)Mapping Fluvial Inundation Extents with Graph Signal Filtering of River Depths Determined from Unsupervised Clustering of Synthetic Aperture Radar Imagery., and . IGARSS, page 6124-6127. IEEE, (2021)Near-Real Time Crop Progress Estimation using Remote Sensing in Regions without Ground Survey Data., and . IGARSS, page 5456-5459. IEEE, (2022)Integrating Time Series Remote Sensing Information in Suitability Analysis for Land Use Planning., , , and . IGARSS, page 6372-6375. IEEE, (2022)