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

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 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.

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Keywords

  • 3D reconstruction
  • <i>Cunninghamia</i>
  • 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, sampling design
  • 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 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
  • 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

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