Shi, Jiancheng||Liang, Shunlin||Yan, Guangjian <br/><br/>
Advances in Quantitative Remote Sensing in China – In Memory of Prof. Xiaowen Li 

<br/><br/><br/>English[eng] 
<br/><br/><label>Subjects--Topical Terms: </label><br/>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