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Classifying the Canadian Boreal forest's structure using multi-modal remote sensing.

, , , and . IGARSS, page 5329-5332. IEEE, (2012)

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Model-based estimation of large area forest canopy height and biomass using radar and optical remote sensing with limited lidar data., , and . IGARSS, page 1016-1019. IEEE, (2017)Quantifying the results of wind and rain on ifsar tree height estimation., , and . IGARSS, page 3275-3278. IEEE, (2010)Exploring the Canadian boreal forest using airsar, LandSAT5, and virtual lidar., , and . IGARSS, page 1741-1744. IEEE, (2016)Extrapolation of LiDAR for forest structure estimation using SAR, InSAR, and optical data., , , , , and . IGARSS, page 1633-1636. IEEE, (2010)Variable Wind Influence on InSAR Imagery of Forests., , and . IGARSS (4), page 141-144. IEEE, (2009)Estimating the three dimensional structure of the harvard forest using a database driven multi-modal remote sensing technique., , and . IGARSS, page 5814-5817. IEEE, (2017)Quantifying the Effect of the Wind on Trees Observed by Synthetic Aperture Radar Systems., , and . IGARSS, page 6677-6680. IEEE, (2021)Estimating the ground heightwith L-band IfSAR in a wind-blown forest environment., , and . IGARSS, page 1119-1122. IEEE, (2013)Estimating boreal forest canopy height and above ground biomass using multi-modal remote sensing; a database driven approach., , and . IGARSS, page 2498-2501. IEEE, (2016)Estimating the three dimensional structure of heterogeneous forests using multi-modal remote sensing and sensor extrapolation techniques., , and . IGARSS, page 2502-2505. IEEE, (2016)