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The principal aim of this book is to provide a wide range of information and a useful reference for researchers interested to investigate heavy mineral assemblages in different geological settings and for a variety of purposes. The methodological developments achieved in recent years for the identification of heavy minerals in a wide grain-size range are illustrated. All factors that affect heavy mineral concentration and relative proportions, including hydraulic sorting, mechanical abrasion, chemical weathering, and post-depositional dissolution, and all factors able to introduce analytical, environmental, or diagenetic bias are thoroughly addressed. A proper integration of multiple techniques including bulk sediment, multi-mineral, and single-mineral methods are discussed by renowned authors in their invited contributions.

heavy minerals --- correlation --- North Sea --- Jurassic --- Triassic --- Carboniferous --- Devonian --- relative and absolute abundances --- sampling strategy --- size-window for analysis --- heavy mineral point-counting --- provenance and plate-tectonic setting --- chemical weathering --- hydraulic sorting --- recycling --- diagenesis --- sediment --- provenance --- statistics --- zircon --- point counting --- petrography --- mineral grains composition --- surface textures --- sources --- WNW Portuguese Continental Margin --- Raman spectroscopy --- sedimentary provenance --- automatization --- heavy mineral --- Pliocene --- the Changjiang Delta --- amphibole --- surface texture --- garnet --- epidote --- pyroxene --- provenance tracers --- varietal studies --- mineral chemistry --- semi-automated Raman counting --- Ladakh-Kohistan arcs --- Himalaya --- Nanga Parbat --- Karakorum --- Indus river --- amphiboles --- tremolite --- actinolite --- provenance analysis --- tectonic versus climatic control --- early-middle Pleistocene transition --- Yellow River terraces --- Lanzhou (northern China) --- sieving of fine silt --- fallacy of laser granulometry --- benthic foraminifera --- Ganga–Brahmaputra river system --- Bay of Bengal --- Himalayan orogen --- bulk-sediment petrography --- bulk-sediment geochemistry --- selective entrainment --- suspension sorting --- chemical indices of weathering --- sediment budgets --- Brahmaputra River --- Ganga River --- handbook for laboratory procedures --- nontoxic heavy liquids --- wet sieving of silt --- zircon separation --- heavy-mineral mounts --- n/a --- Ganga-Brahmaputra river system

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The principal aim of this book is to provide a wide range of information and a useful reference for researchers interested to investigate heavy mineral assemblages in different geological settings and for a variety of purposes. The methodological developments achieved in recent years for the identification of heavy minerals in a wide grain-size range are illustrated. All factors that affect heavy mineral concentration and relative proportions, including hydraulic sorting, mechanical abrasion, chemical weathering, and post-depositional dissolution, and all factors able to introduce analytical, environmental, or diagenetic bias are thoroughly addressed. A proper integration of multiple techniques including bulk sediment, multi-mineral, and single-mineral methods are discussed by renowned authors in their invited contributions.

Research & information: general --- heavy minerals --- correlation --- North Sea --- Jurassic --- Triassic --- Carboniferous --- Devonian --- relative and absolute abundances --- sampling strategy --- size-window for analysis --- heavy mineral point-counting --- provenance and plate-tectonic setting --- chemical weathering --- hydraulic sorting --- recycling --- diagenesis --- sediment --- provenance --- statistics --- zircon --- point counting --- petrography --- mineral grains composition --- surface textures --- sources --- WNW Portuguese Continental Margin --- Raman spectroscopy --- sedimentary provenance --- automatization --- heavy mineral --- Pliocene --- the Changjiang Delta --- amphibole --- surface texture --- garnet --- epidote --- pyroxene --- provenance tracers --- varietal studies --- mineral chemistry --- semi-automated Raman counting --- Ladakh-Kohistan arcs --- Himalaya --- Nanga Parbat --- Karakorum --- Indus river --- amphiboles --- tremolite --- actinolite --- provenance analysis --- tectonic versus climatic control --- early-middle Pleistocene transition --- Yellow River terraces --- Lanzhou (northern China) --- sieving of fine silt --- fallacy of laser granulometry --- benthic foraminifera --- Ganga-Brahmaputra river system --- Bay of Bengal --- Himalayan orogen --- bulk-sediment petrography --- bulk-sediment geochemistry --- selective entrainment --- suspension sorting --- chemical indices of weathering --- sediment budgets --- Brahmaputra River --- Ganga River --- handbook for laboratory procedures --- nontoxic heavy liquids --- wet sieving of silt --- zircon separation --- heavy-mineral mounts

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• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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.

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 --- Cunninghamia --- 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 --- South China's --- MS-PT algorithm

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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.

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 --- Cunninghamia --- 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 --- South China's --- MS-PT algorithm

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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.

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 --- Cunninghamia --- 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 --- 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