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Remote Sensing of Biophysical Parameters
Remote Sensing of Biophysical Parameters
Autore García-Haro Francisco Javier
Descrizione fisica 1 online resource (274 p.)
Soggetto topico Research & information: general
Soggetto non controllato 6SV
active learning
agriculture
airborne laser scanning (ALS)
artificial neural networks
ASD Field Spec
biophysical parameters (LAI
burn severity
canopy chlorophyll content
canopy loss
canopy water content
CCC
climate data records (CDR)
clumping index (CI)
Discrete Anisotropic Radiative Transfer (DART) model
EnMAP
equivalent water thickness
FAPAR
FAPAR)
fluorescence
forest
fraction of photosynthetically active radiation absorbed by vegetation (FPAR)
FVC
GPR
hyperspectral
in vivo
INFORM
invasive vegetation
LAI
Landsat 8
LaSRC
LCC
lead ions
leaf area index
leaf area index (LAI)
LEDAPS
machine learning
meteosat second generation (MSG)
Moderate Resolution Imaging Spectroradiometer (MODIS)
MODIS
multispectral sensor
NDVI
PROSAIL
rapeseed crop
remote sensing indices
riparian
SAIL
Satellite Application Facility for Land Surface Analysis (LSA SAF)
Sentinel-2
SEVIRI
site-specific farming
soil albedo
spaceborne laser scanning (SLS)
spectrometry
spectroscopy
SREM
stochastic spectral mixture model (SSMM)
surface reflectance
terrestrial laser scanning (TLS)
the fraction of radiation absorbed by photosynthetic components (FAPARgreen)
three-dimensional radiative transfer model (3D RTM)
triple-source
uncertainty assessment
unmanned aircraft vehicle
vegetation indices
vegetation radiative transfer model
vertical foliage profile (VFP)
wildfire
woody area index (WAI)
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910595067603321
García-Haro Francisco Javier  
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters / Hongliang Fang, Juanma Lopez Sanchez, Francisco Javier García-Haro
Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters / Hongliang Fang, Juanma Lopez Sanchez, Francisco Javier García-Haro
Autore Fang Hongliang
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica 1 electronic resource (334 p.)
Soggetto non controllato artificial neural network
downscaling
simulation
3D point cloud
European beech
consistency
adaptive threshold
evaluation
photosynthesis
geographic information system
P-band PolInSAR
validation
density-based clustering
structure from motion (SfM)
EPIC
Tanzania
signal attenuation
trunk
canopy closure
REDD+
unmanned aerial vehicle (UAV)
forest
recursive feature elimination
Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR)
aboveground biomass
random forest
uncertainty
household survey
spectral information
forests biomass
root biomass
biomass
unmanned aerial vehicle
Brazilian Amazon
VIIRS
global positioning system
LAI
photochemical reflectance index (PRI)
allometric scaling and resource limitation
R690/R630
modelling aboveground biomass
leaf area index
forest degradation
spectral analyses
terrestrial laser scanning
BAAPA
leaf area index (LAI)
stem volume estimation
tomographic profiles
polarization coherence tomography (PCT)
canopy gap fraction
automated classification
HemiView
remote sensing
multisource remote sensing
Pléiades imagery
photogrammetric point cloud
farm types
terrestrial LiDAR
altitude
RapidEye
forest aboveground biomass
recovery
southern U.S. forests
NDVI
machine-learning
conifer forest
satellite
chlorophyll fluorescence (ChlF)
tree heights
phenology
point cloud
local maxima
clumping index
MODIS
digital aerial photograph
Mediterranean
hemispherical sky-oriented photo
managed temperate coniferous forests
fixed tree window size
drought
GLAS
smartphone-based method
forest above ground biomass (AGB)
forest inventory
over and understory cover
sampling design
ISBN 9783039212408
3039212400
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910367563203321
Fang Hongliang  
MDPI - Multidisciplinary Digital Publishing Institute, 2019
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui