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

• Andere auteurs: Aranha, José (Redacteur)
• Formaat: Elektronisch Hoofdstuk
• Taal: Engels
• Gepubliceerd in: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Onderwerpen: Research & information: general; Geography; 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
• Online toegang: DOAB: download the publication; DOAB: description of the publication

This Special Issue (SI), entitled "Applications of Remote Sensing Data in Mapping of Forest Growing Stock and Biomass", resulted from 13 peer-reviewed papers dedicated to Forestry and Biomass mapping, characterization and accounting. The papers' authors presented improvements in Remot...