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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 online resource (276 p.)
Soggetto topico Geography
Research and information: general
Soggetto non controllato above-ground biomass
aboveground biomass
AGB estimation and mapping
allometric equation
ALOS DSM
ALOS-2 L band SAR
bark roughness
bioenergy
biomass density
biomass estimation
DBH
diameter at breast height
ecosystem services
forest AGC estimation
forest biomass estimation
forest growing stock volume
forest inventory data
forest succession
forest type
GEOMON
GIS
individual tree detection
landsat
Landsat 8 OLI
Landsat dataset
leaf area index
LiDAR
machine learning
machine learning algorithms
mangroves
map quality
multiple ES interactions
multisource remote sensing
nondestructive method
norway spruce
ordinary kriging
Pinus massoniana plantations
plant area index
random forest
remote sensing
seasonal images
sentinel 2
Sentinel-1 C band SAR
Sentinel-2 MSI
Sentinel-2A
shrubs biomass
spatiotemporal evolution
SPOT6 imagery
stand volume
stepwise regression
subtropical forest
subtropical forests
support vector machine for regression
synergy
terrestrial laser scanning
trade-off
tree height
UAV LiDAR
urban vegetation
valley basin
variable selection
vegetation indices
WorldView-2
Xuzhou
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 online resource (296 p.)
Soggetto topico Research & information: general
Soggetto non controllato accuracy assessment
airborne laser scanning
analytic hierarchy process
anthropogenic
Artic
bark beetle
bark beetle infestation
beech-fir forests
canopy gaps
canopy openings percentage
change detection
damage mapping
deep learning
deforestation depletion
DEM
DJI drone
earth observations
efficiency
Elastic Net
forest canopy
forest classification
forest damage
forest disturbance
forest inventory
forest management
forest mask
forest monitoring
forest road inventory
forested catchment
forestry
GIS
global navigation satellite system
gray level cooccurrence matrix (GLCM)
growing stock volume
harmonic regression
hydrological modeling
Ips typographus L.
Landsat
landsat time series
Large Scale Mean-Shift Segmentation (LSMS)
machine learning
mangrove
mangrove sustainability
MaxENT
multi-scale analysis
multi-temporal regression
multispectral imagery
n/a
national forest inventory
natural water balance
pest
phenology modelling
Phoracantha spp
pixel-based supervised classification
point cloud
positional accuracy
precision density
principal component analysis (PCA)
probability sampling
random forest
Random Forest (RF)
remote sensing
replanting
restoration
risk modeling
satellite imagery
satellite indices
Sentinel-2
Siberia
Southeast Asia
spruce
stand volume
support vector machine
SWAT model
thresholding analysis
time series analysis
total station
UAV
unmanned aerial vehicle (UAV)
validation
vegetation index
wildfires
WorldView-3
Yakutia
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