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The aim of the Special Issue “Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences” was to present a selection of innovative studies using hyperspectral imaging (HSI) in different thematic fields. This intention reflects the technical developments in the last three decades, which have brought the capacity of HSI to provide spectrally, spatially and temporally detailed data, favoured by e.g., hyperspectral snapshot technologies, miniaturized hyperspectral sensors and hyperspectral microscopy imaging. The present book comprises a suite of papers in various fields of environmental sciences—geology/mineral exploration, digital soil mapping, mapping and characterization of vegetation, and sensing of water bodies (including under-ice and underwater applications). In addition, there are two rather methodically/technically-oriented contributions dealing with the optimized processing of UAV data and on the design and test of a multi-channel optical receiver for ground-based applications. All in all, this compilation documents that HSI is a multi-faceted research topic and will remain so in the future.

Research & information: general --- hyperspectral --- topographic correction --- atmospheric correction --- radiometric correction --- long-range --- long-distance --- Structure from Motion (SfM) --- photogrammetry --- mineral mapping --- minimum wavelength mapping --- Maarmorilik --- Riotinto --- Hyperspectral image --- bio-optical algorithm --- phycocyanin --- chlorophyll-a --- mangrove species classification --- close-range hyperspectral imaging --- field hyperspectral measurement --- waveband selection --- machine learning --- instrument development --- spectroradiometry --- telescope --- receiver --- soil --- soil salinity --- unmanned aerial vehicle --- hyperspectral imager --- random forest regression --- electromagnetic induction --- hyperspectral imaging --- tree species --- multiple classifier fusion --- convolutional neural network --- random forest --- rotation forest --- sea ice --- ice algae --- biomass --- fine-scale --- under-ice --- underwater --- antarctica --- structure from motion --- georectification --- mosaicking --- push-broom --- UAV --- chlorophyll a --- colored dissolved organic matter --- in situ measurements --- vertical distribution --- water column --- snapshot hyperspectral imaging --- n/a

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

The aim of the Special Issue “Hyperspectral Imaging for Fine to Medium Scale Applications in Environmental Sciences” was to present a selection of innovative studies using hyperspectral imaging (HSI) in different thematic fields. This intention reflects the technical developments in the last three decades, which have brought the capacity of HSI to provide spectrally, spatially and temporally detailed data, favoured by e.g., hyperspectral snapshot technologies, miniaturized hyperspectral sensors and hyperspectral microscopy imaging. The present book comprises a suite of papers in various fields of environmental sciences—geology/mineral exploration, digital soil mapping, mapping and characterization of vegetation, and sensing of water bodies (including under-ice and underwater applications). In addition, there are two rather methodically/technically-oriented contributions dealing with the optimized processing of UAV data and on the design and test of a multi-channel optical receiver for ground-based applications. All in all, this compilation documents that HSI is a multi-faceted research topic and will remain so in the future.

hyperspectral --- topographic correction --- atmospheric correction --- radiometric correction --- long-range --- long-distance --- Structure from Motion (SfM) --- photogrammetry --- mineral mapping --- minimum wavelength mapping --- Maarmorilik --- Riotinto --- Hyperspectral image --- bio-optical algorithm --- phycocyanin --- chlorophyll-a --- mangrove species classification --- close-range hyperspectral imaging --- field hyperspectral measurement --- waveband selection --- machine learning --- instrument development --- spectroradiometry --- telescope --- receiver --- soil --- soil salinity --- unmanned aerial vehicle --- hyperspectral imager --- random forest regression --- electromagnetic induction --- hyperspectral imaging --- tree species --- multiple classifier fusion --- convolutional neural network --- random forest --- rotation forest --- sea ice --- ice algae --- biomass --- fine-scale --- under-ice --- underwater --- antarctica --- structure from motion --- georectification --- mosaicking --- push-broom --- UAV --- chlorophyll a --- colored dissolved organic matter --- in situ measurements --- vertical distribution --- water column --- snapshot hyperspectral imaging --- n/a

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This book shows recent and innovative applications of the use of hyperspectral technology for optimal quantification of crop, vegetation, and soil biophysical variables at various spatial scales, which can be an important aspect in agricultural management practices and monitoring. The articles collected inside the book are intended to help researchers and farmers involved in precision agriculture techniques and practices, as well as in plant nutrient prediction, to a higher comprehension of strengths and limitations of the application of hyperspectral imaging to agriculture and vegetation. Hyperspectral remote sensing for studying agriculture and natural vegetation is a challenging research topic that will remain of great interest for different sciences communities in decades.

Research & information: general --- Environmental economics --- hyperspectral LiDAR --- Red Edge --- AOTF --- vegetation parameters --- leaf chlorophyll content --- DLARI --- MDATT --- adaxial --- abaxial --- spectral reflectance --- peanut --- field spectroscopy --- hyperspectral --- heavy metals --- grapevine --- PLS --- SVM --- MLR --- multi-angle observation --- hyperspectral remote sensing --- BRDF --- vegetation classification --- object-oriented segmentation --- spectroscopy --- artificial intelligence --- proximal sensing data --- precision agriculture --- spectra --- vegetation --- plant --- classification --- discrimination --- feature selection --- waveband selection --- support vector machine --- random forest --- Natura 2000 --- invasive species --- expansive species --- biodiversity --- proximal sensor --- macronutrient --- micronutrient --- remote sensing --- hyperspectral imaging --- platforms and sensors --- analytical methods --- crop properties --- soil characteristics --- classification of agricultural features --- canopy spectra --- chlorophyll content --- continuous wavelet transform (CWT) --- correlation coefficient --- partial least square regression (PLSR) --- reproducibility --- replicability --- partial least squares --- Ethiopia --- Eragrostis tef --- hyperspectral remote sensing for soil and crops in agriculture --- hyperspectral imaging for vegetation --- plant traits --- high-resolution spectroscopy for agricultural soils and vegetation --- hyperspectral databases for agricultural soils and vegetation --- hyperspectral data as input for modelling soil, crop, and vegetation --- product validation --- new hyperspectral technologies --- future hyperspectral missions