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Applications of Remote Sensing Data in Mapping of Forest Growing Stock and Biomass

Resumen/Descripción – provisto por la editorial

No disponible.

Palabras clave – provistas por la editorial

AGB estimation and mapping; mangroves; UAV LiDAR; WorldView-2; terrestrial laser scanning; above-ground biomass; nondestructive method; DBH; bark roughness; Landsat dataset; forest AGC estimation; random forest; spatiotemporal evolution; aboveground biomass; variable selection; forest type; machine learning; subtropical forests; Landsat 8 OLI; seasonal images; stepwise regression; map quality; subtropical forest; urban vegetation; biomass estimation; Sentinel-2A; Xuzhou; forest biomass estimation; forest inventory data; multisource remote sensing; biomass density; ecosystem services; trade-off; synergy; multiple ES interactions; valley basin; norway spruce; LiDAR; allometric equation; individual tree detection; tree height; diameter at breast height; GEOMON; ALOS-2 L band SAR; Sentinel-1 C band SAR; Sentinel-2 MSI; ALOS DSM; stand volume; support vector machine for regression; ordinary kriging; forest succession; leaf area index; plant area index; machine learning algorithms; forest growing stock volume; SPOT6 imagery; Pinus massoniana plantations; sentinel 2; landsat; remote sensing; GIS; shrubs biomass; bioenergy; vegetation indices

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Información

Tipo de recurso:

libros

ISBN electrónico

978-3-0365-0569-5

País de edición

Suiza