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Book
Advances in Hyperspectral Data Exploitation
Authors: --- --- --- --- --- et al.
ISBN: 3036557962 3036557954 Year: 2022 Publisher: Basel MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

Using hyperspectral imaging (HSI) to exploit data has been found in a wide variety of applications. This reprint book only presents a small glimpse of it. Many other important applications using HSI which have emerged in data exploitation are not covered in this reprint book. For example, such applications may include water pollution and toxic waste in environmental monitoring, pesticide residual detection in food safety and inspection, plant and crop disease detection in agriculture, tumor detection and breast cancer detection in medical imaging, drug traffic in law enforcement, etc. Nevertheless, this reprint book provides many techniques which may find their ways in these applications as well.

Keywords

Technology: general issues --- History of engineering & technology --- hyperspectral image few-shot classification --- deep learning --- meta-learning --- relation network --- convolutional neural network --- constrained-target optimal index factor band selection (CTOIFBS) --- hyperspectral image --- underwater spectral imaging system --- underwater hyperspectral target detection --- band selection (BS) --- constrained energy minimization (CEM) --- lightweight convolutional neural networks --- hyperspectral imagery classification --- transfer learning --- air temperature --- spatial measurement --- FTIR --- MWIR --- carbon dioxide absorption --- target detection --- coffee beans --- insect damage --- hyperspectral imaging --- band selection --- visualization --- color formation models --- multispectral image --- image fusion --- joint tensor decomposition --- anomaly detection --- constrained sparse representation --- hyperspectral imagery --- moving target detection --- spatio-temporal processing --- hyperspectral remote sensing --- image classification --- constraint representation --- superpixel segmentation --- multiscale decision fusion --- plug-and-play --- denoising --- nonlinear unmixing --- spectral reconstruction --- residual augmented attentional u-shape network --- spatial augmented attention --- channel augmented attention --- boundary-aware constraint --- atmospheric transmittance --- temperature --- emissivity --- separation --- midwave infrared --- hyperspectral images --- hyperspectral image super-resolution --- data fusion --- spectral-spatial residual network --- self-supervised training --- hyperspectral --- vegetation --- generative adversarial network --- data augmentation --- classification --- rice leaf blast --- hyperspectral imaging data --- deep convolutional neural networks --- fused features --- evolutionary computation --- heuristic algorithms --- machine learning --- unmanned aerial vehicles (UAVs) --- vegetation mapping --- upland swamps --- mine environment --- rice --- rice leaf folder --- hyperspectral image classification --- change detection --- self-supervised learning --- attention mechanism --- multi-source image fusion --- SFIM --- least square estimation --- spatial filter --- hyperspectral imaging (HSI) --- hyperspectral target detection --- hyperspectral reconstruction --- hyperspectral unmixing


Book
Applications of Remote Sensing in Coastal Areas
Authors: --- --- --- ---
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

Coastal areas are remarkable regions with high spatiotemporal variability. A large population is affected by their physical and biological processes—resulting from effects on tourism to biodiversity and productivity. Coastal ecosystems perform several critical ecosystem services and functions, such as water oxygenation and nutrients provision, seafloor and beach stabilization (as sediment is controlled and trapped within the rhizomes of the seagrass meadows), carbon burial, as areas for nursery, and as refuge for several commercial and endemic species. Knowledge of the spatial distribution of marine habitats is prerequisite information for the conservation and sustainable use of marine resources. Remote sensing from UAVs to spaceborne sensors is offering a unique opportunity to measure, analyze, quantify, map, and explore the processes on the coastal areas at high temporal frequencies. This Special Issue on “Application of Remote Sensing in Coastal Areas” is specifically addresses those successful applications—from local to regional scale—in coastal environments related to ecosystem productivity, biodiversity, sea level rise.

Keywords

satellite remote sensing --- Landsat --- coastline --- barrier island --- morphological change --- coastal ocean --- Photon-counting lidar --- MABEL --- land cover --- remote sensing --- signal photons --- ground settlement --- marine reclamation land --- time series InSAR --- Sentinel-1 --- Xiamen New Airport --- Pleiades --- photogrammetry --- LiDAR --- RTK-GPS --- beach topography --- cliff coastlines --- time-series analysis --- terrestrial laser scanner --- southern Baltic Sea --- non-parametric Bayesian network --- satellite-derived bathymetry --- hydrography --- CubeSats --- hypertemporal --- zones of confidence --- PlanetScope --- vegetation mapping --- dunes --- unmanned aerial system --- pixel-based classification --- object-based classification --- dune vegetation classification --- coastal monitoring --- multispectral satellite images --- multi-temporal NDVI --- pixels based supervised classification --- Random Forest --- harmonization --- shoreline mapping --- semi-global subpixel localization --- intensity integral error --- polarimetric SAR --- polarimetric decomposition --- ship detection --- Euclidean distance --- mutual information --- new feature --- Bohai sea ice --- sea ice extent --- OLCI imagery --- sea ice information index --- waterline extraction --- sub-pixel --- surface water mapping --- data cube --- contour extraction --- water extraction --- water indices --- thresholding --- Coastal process --- wind wake --- heat advection --- multi-sensor --- ASAR --- oceanic thermal response --- Hainan Island --- coastal remote sensing --- habitat mapping --- unmanned aerial vehicle (UAV) --- unmanned aircraft system (UAS) --- drone --- object-based image analysis (OBIA) --- UAS data acquisition --- n/a

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