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Advances in Quantitative Remote Sensing in China - In Memory of Prof. Xiaowen Li



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Autore: Shi Jiancheng Visualizza persona
Titolo: Advances in Quantitative Remote Sensing in China - In Memory of Prof. Xiaowen Li Visualizza cluster
Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2019
Descrizione fisica: 1 online resource (404 p.)
Soggetto topico: Geography
Soggetto non controllato: <i>Cunninghamia</i>
3D reconstruction
aboveground biomass
aerosol
aerosol retrieval
albedometer
algorithmic assessment
AMSR2
anisotropic reflectance
Antarctica
arid/semiarid
AVHRR
BEPS
biodiversity
black-sky albedo (BSA)
boreal forest
BRDF
canopy reflectance
China
Chinese fir
cloud fraction
CMA
composite slope
comprehensive field experiment
controlling factors
copper
cost-efficient
crop-growing regions
daily average value
decision tree
dense forest
disturbance index
downscaling
downward shortwave radiation
drought
end of growing season (EOS)
evapotranspiration
EVI2
fluorescence quantum efficiency in dark-adapted conditions (FQE)
flux measurements
forest canopy height
forest disturbance
fractional vegetation cover (FVC)
Fraunhofer Line Discrimination (FLD)
FY-3C/MERSI
FY-3C/MWRI
gap fraction
geographical detector model
geometric optical radiative transfer (GORT) model
geometric-optical model
geostationary satellite
GF-1 WFV
GLASS
GLASS LAI time series
GPP
gradient boosting regression tree
gross primary production (GPP)
gross primary productivity (GPP)
heterogeneity
high resolution
high-resolution freeze/thaw
HiWATER
HJ-1 CCD
homogeneous and pure pixel filter
humidity profiles
hybrid method
ICESat GLAS
inter-annual variation
interference filter
interpolation
LAI
land cover change
land surface albedo
Land surface emissivity
land surface temperature
Land surface temperature
land surface variables
land-surface temperature products (LSTs)
Landsat
latent heat
latitudinal pattern
leaf
leaf age
leaf area density
leaf area index
leaf spectral properties
LiDAR
light use efficiency
longwave upwelling radiation (LWUP)
LUT method
machine learning
machine learning algorithms
maize
MCD43A3 C6
meteorological factors
metric comparison
metric integration
MODIS
MODIS products
MRT-based model
MS-PT algorithm
multi-data set
multi-scale validation
multiple ecological factors
multisource data fusion
MuSyQ-GPP algorithm
n/a
NDVI
NIR
Northeast China
northern China
NPP
observations
passive microwave
phenological parameters
phenology
photoelectric detector
pixel unmixing
plant functional type
point cloud
polar orbiting satellite
potential evapotranspiration
precipitation
probability density function
PROSPECT
PROSPECT-5B+SAILH (PROSAIL) model
quantitative remote sensing inversion
RADARSAT-2
random forest model
reflectance model
remote sensing
rice
rugged terrain
sampling design
satellite observations
scale effects
SCOPE
SIF
sinusoidal method
snow cover
snow-free albedo
solar-induced chlorophyll fluorescence
solo slope
South China's
spatial heterogeneity
spatial representativeness
spatial-temporal variations
spatio-temporal
spatiotemporal distribution and variation
spatiotemporal representative
species richness
spectra
spectral
SPI
standard error of the mean
start of growing season (SOS)
statistics methods
subpixel information
sunphotometer
surface radiation budget
surface solar irradiance
SURFRAD
Synthetic Aperture Radar (SAR)
temperature profiles
terrestrial LiDAR
thermal radiation directionality
Tibetan Plateau
TMI data
topographic effects
tree canopy
uncertainty
urban scale
validation
variability
vegetation dust-retention
vegetation phenology
vegetation remote sensing
vertical structure
vertical vegetation stratification
Visible Infrared Imaging Radiometer Suite (VIIRS)
voxel
VPM
ZY-3 MUX
Persona (resp. second.): LiangShunlin
YanGuangjian
Sommario/riassunto: Quantitative land remote sensing has recently advanced dramatically, particularly in China. It has been largely driven by vast governmental investment, the availability of a huge amount of Chinese satellite data, geospatial information requirements for addressing pressing environmental issues and other societal benefits. Many individuals have also fostered and made great contributions to its development, and Prof. Xiaowen Li was one of these leading figures. This book is published in memory of Prof. Li. The papers collected in this book cover topics from surface reflectance simulation, inversion algorithm and estimation of variables, to applications in optical, thermal, Lidar and microwave remote sensing. The wide range of variables include directional reflectance, chlorophyll fluorescence, aerosol optical depth, incident solar radiation, albedo, surface temperature, upward longwave radiation, leaf area index, fractional vegetation cover, forest biomass, precipitation, evapotranspiration, freeze/thaw snow cover, vegetation productivity, phenology and biodiversity indicators. They clearly reflect the current level of research in this area. This book constitutes an excellent reference suitable for upper-level undergraduate students, graduate students and professionals in remote sensing.
Titolo autorizzato: Advances in Quantitative Remote Sensing in China – In Memory of Prof. Xiaowen Li  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910346664203321
Lo trovi qui: Univ. Federico II
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