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Potential of L-Band Radar for Retrieval of Canopy and Subcanopy Parameters of Boreal Forests.

, , and . IEEE Trans. Geosci. Remote. Sens., 50 (6): 2150-2160 (2012)

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The importance of forest spatial heterogeneity: Exploring the effect of mix scenes using coherence three-dimension radar backscattering model., , and . IGARSS, page 732-735. IEEE, (2016)Advancing NASA's AirMOSS P-Band Radar Root Zone Soil Moisture Retrieval Algorithm via Incorporation of Richards' Equation., , , , and . Remote Sensing, 9 (1): 17 (2017)3-D Level Set Method for Joint Contrast and Shape Recovery in Microwave Imaging., , , and . IEEE Trans. Computational Imaging, 5 (1): 97-108 (2019)Relationship Between Bistatic Radar Scattering Cross Sections and GPS Reflectometry Delay-Doppler Maps Over Vegetated Land in Support of Soil Moisture Retrieval., , and . IGARSS, page 7480-7482. IEEE, (2018)Retrieving Root-Zone Soil Moisture Profile From P-Band Radar via Hybrid Global and Local Optimization., , and . IEEE Trans. Geosci. Remote. Sens., 58 (8): 5400-5408 (2020)Forest parameter retrieval from SAR data using an estimation algorithm applied to regrowing forest stands in Queensland, Australia., , , , , and . IGARSS, page 1238-1241. IEEE, (2010)Retrieval of forest structure and moisture from SAR data using an estimation algorithm., , , and . IGARSS, page 153-156. IEEE, (2013)Decomposing soil and vegetation contributions in polarimetric L- and P- band SAR observations., , , and . IGARSS, page 7553-7556. IEEE, (2016)Joint-physics emission-scattering model for improved active-passive soil moisture estimation., and . IGARSS, page 1885-1887. IEEE, (2016)Proposed investigations from NASA's Earth Venture-1 (EV-1) airborne science selections., , , , , , and . IGARSS, page 2575-2578. IEEE, (2010)