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Climate-Change-Driven Droughts and Tree Mortality: Assessing the Potential of UAV-Derived Early Warning Metrics., , , , , , , , , and 12 other author(s). Remote. Sens., 15 (10): 2627 (2023)Crown-Level Structure and Fuel Load Characterization from Airborne and Terrestrial Laser Scanning in a Longleaf Pine (Pinus palustris Mill.) Forest Ecosystem., , , , , , , , , and 6 other author(s). Remote. Sens., 15 (4): 1002 (February 2023)Regional Tropical Aboveground Biomass Mapping with L-Band Repeat-Pass Interferometric Radar, Sparse Lidar, and Multiscale Superpixels., , , , , , , , and . Remote. Sens., 12 (12): 2048 (2020)Post-Hurricane Damage Severity Classification at the Individual Tree Level Using Terrestrial Laser Scanning and Deep Learning., , , , , , and . Remote. Sens., 15 (4): 1165 (February 2023)Monitoring the structure of forest restoration plantations with a drone-lidar system., , , , , , , , , and 3 other author(s). Int. J. Appl. Earth Obs. Geoinformation, (2019)A Regional L-Band High Biomass Estimation Framework Leveraging Spaceborne Lidar and Interferometric Data to Overcome Backscatter Saturation., , , , , and . IGARSS, page 4991-4994. IEEE, (2020)Forest inventory with high-density UAV-Lidar: Machine learning approaches for predicting individual tree attributes., , , , , , , , , and 5 other author(s). Comput. Electron. Agric., (2020)Estimating Stem Volume in Eucalyptus Plantations Using Airborne LiDAR: A Comparison of Area- and Individual Tree-Based Approaches., , , , , , , , , and . Remote. Sens., 12 (9): 1513 (2020)Forest Aboveground Biomass Estimation with GEDI and ICESat-2 in Boreal Forests., , , , , , , , , and 1 other author(s). IGARSS, page 670-672. IEEE, (2021)Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data., , , , , , , , , and 3 other author(s). Remote. Sens., 12 (9): 1438 (2020)