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

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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 ot...

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محفوظ في:
المؤلفون الرئيسيون: Shi, Jiancheng, Liang, Shunlin, Yan, Guangjian
التنسيق: Online
اللغة:الإنجليزية
منشور في: MDPI - Multidisciplinary Digital Publishing Institute 2021
الموضوعات:
G1-922
Q1-390
gross primary production (GPP)
interference filter
Visible Infrared Imaging Radiometer Suite (VIIRS)
cost-efficient
precipitation
topographic effects
land surface temperature
Land surface emissivity
scale effects
spatial-temporal variations
statistics methods
inter-annual variation
spatial representativeness
FY-3C/MERSI
sunphotometer
PROSPECT
passive microwave
flux measurements
urban scale
vegetation dust-retention
multiple ecological factors
leaf age
standard error of the mean
LUT method
spectra
SURFRAD
Land surface temperature
aboveground biomass
uncertainty
land surface variables
copper
Northeast China
forest disturbance
end of growing season (EOS)
random forest model
probability density function
downward shortwave radiation
machine learning
MODIS products
composite slope
daily average value
canopy reflectance
spatiotemporal representative
light use efficiency
hybrid method
disturbance index
quantitative remote sensing inversion
SCOPE
GPP
South China’s
anisotropic reflectance
vertical structure
snow cover
land cover change
start of growing season (SOS)
MS–PT algorithm
aerosol
pixel unmixing
HiWATER
algorithmic assessment
surface radiation budget
latitudinal pattern
ICESat GLAS
vegetation phenology
SIF
metric comparison
Antarctica
spatial heterogeneity
comprehensive field experiment
reflectance model
sinusoidal method
NDVI
BRDF
cloud fraction
NPP
VPM
China
dense forest
vegetation remote sensing
<i>Cunninghamia</i>
high resolution
geometric-optical model
phenology
LiDAR
ZY-3 MUX
point cloud
multi-scale validation
Fraunhofer Line Discrimination (FLD)
rice
fractional vegetation cover (FVC)
interpolation
high-resolution freeze/thaw
drought
Synthetic Aperture Radar (SAR)
controlling factors
sampling design
downscaling
n/a
Chinese fir
MRT-based model
RADARSAT-2
northern China
leaf area density
potential evapotranspiration
black-sky albedo (BSA)
decision tree
CMA
fluorescence quantum efficiency in dark-adapted conditions (FQE)
surface solar irradiance
validation
geographical detector model
vertical vegetation stratification
spatiotemporal distribution and variation
gap fraction
phenological parameters
spatio-temporal
albedometer
variability
GLASS
gross primary productivity (GPP)
EVI2
machine learning algorithms
latent heat
GLASS LAI time series
boreal forest
leaf
maize
heterogeneity
temperature profiles
crop-growing regions
satellite observations
rugged terrain
species richness
voxel
LAI
TMI data
GF-1 WFV
spectral
HJ-1 CCD
leaf area index
evapotranspiration
land-surface temperature products (LSTs)
SPI
AVHRR
Tibetan Plateau
snow-free albedo
PROSPECT-5B+SAILH (PROSAIL) model
MCD43A3 C6
3D reconstruction
photoelectric detector
multi-data set
BEPS
aerosol retrieval
plant functional type
multisource data fusion
remote sensing
leaf spectral properties
solo slope
land surface albedo
longwave upwelling radiation (LWUP)
terrestrial LiDAR
AMSR2
geometric optical radiative transfer (GORT) model
MuSyQ-GPP algorithm
tree canopy
FY-3C/MWRI
meteorological factors
solar-induced chlorophyll fluorescence
metric integration
observations
polar orbiting satellite
arid/semiarid
homogeneous and pure pixel filter
thermal radiation directionality
biodiversity
gradient boosting regression tree
forest canopy height
Landsat
subpixel information
MODIS
humidity profiles
NIR
geostationary satellite
thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography
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