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Applications of Remote Sensing Data in Mapping of Forest Growing Stock and Biomass
Applications of Remote Sensing Data in Mapping of Forest Growing Stock and Biomass
Autore Aranha José
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (276 p.)
Soggetto topico Research & information: general
Geography
Soggetto non controllato 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
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557474803321
Aranha José  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Operationalization of Remote Sensing Solutions for Sustainable Forest Management
Operationalization of Remote Sensing Solutions for Sustainable Forest Management
Autore Mozgeris Gintautas
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (296 p.)
Soggetto topico Research & information: general
Soggetto non controllato forest road inventory
total station
global navigation satellite system
point cloud
precision density
positional accuracy
efficiency
mangrove sustainability
deforestation depletion
anthropogenic
natural water balance
Southeast Asia
Phoracantha spp
unmanned aerial vehicle (UAV)
multispectral imagery
vegetation index
thresholding analysis
Large Scale Mean-Shift Segmentation (LSMS)
Random Forest (RF)
forest mask
validation
probability sampling
remote sensing
earth observations
forestry
accuracy assessment
forest classification
forested catchment
hydrological modeling
SWAT model
DEM
airborne laser scanning
deep learning
Landsat
national forest inventory
stand volume
bark beetle
Ips typographus L.
pest
change detection
forest damage
spruce
Sentinel-2
damage mapping
multi-temporal regression
mangrove
replanting
restoration
analytic hierarchy process
UAV
DJI drone
machine learning
forest canopy
canopy gaps
canopy openings percentage
satellite indices
Elastic Net
beech-fir forests
pixel-based supervised classification
random forest
support vector machine
gray level cooccurrence matrix (GLCM)
principal component analysis (PCA)
WorldView-3
wildfires
MaxENT
risk modeling
GIS
multi-scale analysis
Yakutia
Artic
Siberia
phenology modelling
forest disturbance
forest monitoring
bark beetle infestation
forest management
time series analysis
satellite imagery
landsat time series
growing stock volume
forest inventory
harmonic regression
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557584103321
Mozgeris Gintautas  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui