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

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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Bibliographic Details
Main Author:	Shi, Jiancheng
Other Authors:	Liang, Shunlin, Yan, Guangjian
Format:	eBook
Language:	English
Published:	MDPI - Multidisciplinary Digital Publishing Institute 2019
Subjects:	Machine Learning Chinese Fir Land-surface Temperature Products (lsts) End Of Growing Season (eos) Musyq-gpp Algorithm Controlling Factors Landsat Comprehensive Field Experiment Land Cover Change Npp Land Surface Albedo Voxel Phenological Parameters Disturbance Index Spi Satellite Observations Tibetan Plateau Forest Canopy Height Brdf Beps Arid/semiarid Homogeneous And Pure Pixel Filter Glass Lai Time Series Aerosol Pixel Unmixing Uncertainty Boreal Forest Variability Multi-data Set Random Forest Model Drought Leaf Area Density Urban Scale Spatial Representativeness Black-sky Albedo (bsa) Interpolation Copper Visible Infrared Imaging Radiometer Suite (viirs) Precipitation Gf-1 Wfv Modis Products Geometric Optical Radiative Transfer (gort) Model <i>cunninghamia</i> Scale Effects Vegetation Dust-retention Multi-scale Validation Sinusoidal Method Prospect-5b+sailh (prosail) Model Polar Orbiting Satellite Sampling Design Surface Radiation Budget Metric Comparison Topographic Effects Flux Measurements Humidity Profiles Spectral Snow Cover Icesat Glas Land Surface Emissivity Interference Filter Vpm Temperature Profiles Lut Method Sif Latitudinal Pattern Probability Density Function Cost-efficient Meteorological Factors Avhrr High-resolution Freeze/thaw Algorithmic Assessment Composite Slope Northern China China Multisource Data Fusion Rice Sunphotometer Rugged Terrain Gross Primary Production (gpp) Fy-3c/mwri Geography / Bicssc Standard Error Of The Mean Latent Heat Maize Quantitative Remote Sensing Inversion Start Of Growing Season (sos) Dense Forest Aerosol Retrieval Validation Anisotropic Reflectance Light Use Efficiency Point Cloud Hiwater Modis Vegetation Phenology 3d Reconstruction Gross Primary Productivity (gpp) Ndvi Hj-1 Ccd Solo Slope Spatio-temporal Vegetation Remote Sensing Evi2 Land Surface Temperature Glass Surfrad Terrestrial Lidar Antarctica Gradient Boosting Regression Tree N/a Prospect Geographical Detector Model Fluorescence Quantum Efficiency In Dark-adapted Conditions (fqe) Geostationary Satellite Fraunhofer Line Discrimination (fld) Spatial Heterogeneity Inter-annual Variation Nir Thermal Radiation Directionality Spatial-temporal Variations Vertical Vegetation Stratification Potential Evapotranspiration Hybrid Method Crop-growing Regions Forest Disturbance Subpixel Information Metric Integration Leaf Spectral Properties Species Richness Fy-3c/mersi Solar-induced Chlorophyll Fluorescence Synthetic Aperture Radar (sar) Reflectance Model Surface Solar Irradiance Multiple Ecological Factors Spectra Spatiotemporal Distribution And Variation Mcd43a3 C6 Observations Tree Canopy High Resolution Daily Average Value Passive Microwave Land Surface Variables Fractional Vegetation Cover (fvc) Gap Fraction Gpp Leaf Area Index Evapotranspiration Machine Learning Algorithms Cloud Fraction Downscaling Lai Geometric-optical Model Amsr2 Ms-pt Algorithm Lidar Remote Sensing Photoelectric Detector Vertical Structure South China's Cma Leaf Age Phenology Biodiversity Radarsat-2 Zy-3 Mux Leaf Heterogeneity Aboveground Biomass Mrt-based Model Decision Tree Snow-free Albedo Northeast China Statistics Methods Scope Plant Functional Type Canopy Reflectance Downward Shortwave Radiation Albedometer Spatiotemporal Representative Longwave Upwelling Radiation (lwup) Tmi Data
Online Access:	https://directory.doabooks.org/handle/20.500.12854... https://www.mdpi.com/books/pdfview/book/1158
Collection:	Directory of Open Access Books - Collection details see MPG.ReNa

Description
Summary:	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.
Item Description:	Creative Commons (cc), https://creativecommons.org/licenses/by-nc-nd/4.0/
Physical Description:	1 electronic resource (404 p.)
ISBN:	books978-3-03897-271-6 9783038972709

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

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