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Spaceborne Lidar and Stereogrammetry Data Fusion to Predict Aboveground Biomass in Tropical Forests., , , , , , , , , and 4 other author(s). IGARSS, page 3592-3595. IEEE, (2024)Correlation between the variations of clay content in soils and sediments and the spectral behavior of superjacent vegetation using spectir hyperspectral images., , , , , and . WHISPERS, page 1-4. IEEE, (2012)Does environmental data increase the accuracy of land use and land cover classification?, , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2020)A Machine Learning approach to reconstruct cloudy affected vegetation indices imagery via data fusion from Sentinel-1 and Landsat 8., , , , and . Comput. Electron. Agric., (2022)Artificial neural networks on integrated multispectral and SAR data for high-performance prediction of eucalyptus biomass., , , , , , , , , and 4 other author(s). Comput. Electron. Agric., (2020)Vegetation chlorophyll estimates in the Amazon from multi-angle MODIS observations and canopy reflectance model., , , , , , , , , and 10 other author(s). Int. J. Appl. Earth Obs. Geoinformation, (2017)Integrating Spaceborne Lidar Nasa's Gedi With Imaging Sensors To Map Aboveground Biomass In Fragmented Tropical Forests., , , , , , , , , and 1 other author(s). IGARSS, page 1887-1889. IEEE, (2023)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)