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Palabras clave – provistas por la editorial

spectral; Cameroon; quantitative structural model; digital hemispherical photograph (DHP); environment effects; human activity; reference level; terrestrial laser scanning; topographic effects; Guyana; predictive mapping; aboveground biomass estimation; geographic information system; Pinus massoniana; 3D tree modelling; ensemble model; destructive sampling; model comparison; topography; remote sensing; forest growing stock volume (GSV); local tree allometry; tree mapping; gray level co-occurrence matrix (GLCM); deforestation; REDD+; sentinel imagery; geographically weighted regression; aboveground biomass; random forest; random forest (RF); silviculture; agriculture; crown density; hazard mapping; model evaluation; old-growth forest; full polarimetric SAR; subtropical forest; forest canopy; forest classification; low-accuracy estimation; texture; LiDAR; Landsat; phenology; airborne laser scanning; tall trees; machine learning; forest baseline; overstory trees; support vector machine; above-ground biomass; multispectral satellite imagery; crown delineation; specific leaf area; forest inventory; canopy cover (CC); voxelization; forestry; leaf area