Remote Sensing Technology Applications in Forestry and REDD+

• 1. Verfasser: Vastaranta, Mikko (auth)
• Weitere Verfasser: Calders, Kim (auth), Jonckheere, Inge (auth), Nightingale, Joanne (auth)
• Format: Elektronisch Buchkapitel
• Sprache: Englisch
• Veröffentlicht: MDPI - Multidisciplinary Digital Publishing Institute 2020
• Schlagworte: Environmental science, engineering & technology; 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
• Online-Zugang: DOAB: download the publication; DOAB: description of the publication

Advances in close-range and remote sensing technologies are driving innovations in forest resource assessments and monitoring on varying scales. Data acquired with airborne and spaceborne platforms provide high(er) spatial resolution, more frequent coverage, and more spectral information. Recent dev...