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Each year, natural hazards such as earthquakes, cyclones, flooding, landslides, wildfires, avalanches, volcanic eruption, extreme temperatures, storm surges, drought, etc., result in widespread loss of life, livelihood, and critical infrastructure globally. With the unprecedented growth of the human population, largescale development activities, and changes to the natural environment, the frequency and intensity of extreme natural events and consequent impacts are expected to increase in the future.Technological interventions provide essential provisions for the prevention and mitigation of natural hazards. The data obtained through remote sensing systems with varied spatial, spectral, and temporal resolutions particularly provide prospects for furthering knowledge on spatiotemporal patterns and forecasting of natural hazards. The collection of data using earth observation systems has been valuable for alleviating the adverse effects of natural hazards, especially with their near real-time capabilities for tracking extreme natural events. Remote sensing systems from different platforms also serve as an important decision-support tool for devising response strategies, coordinating rescue operations, and making damage and loss estimations.With these in mind, this book seeks original contributions to the advanced applications of remote sensing and geographic information systems (GIS) techniques in understanding various dimensions of natural hazards through new theory, data products, and robust approaches.

sequential estimation --- InSAR time series --- groundwater --- land subsidence and rebound --- earthquake --- rapid mapping --- damage assessment --- deep learning --- convolutional neural networks --- ordinal regression --- aerial image --- landslide --- machine learning models --- remote sensing --- ensemble models --- validation --- ice storm --- forest ecosystems --- disaster impact --- post-disaster recovery --- ice jam --- snowmelt --- flood mapping --- monitoring and prediction --- VIIRS --- ABI --- NUAE --- flash flood --- BRT --- CART --- naive Bayes tree --- geohydrological model --- landslide susceptibility --- Bangladesh --- digital elevation model --- random forest --- modified frequency ratio --- logistic regression --- automatic landslide detection --- OBIA --- PBA --- random forests --- supervised classification --- landslides --- uncertainty --- K-Nearest Neighbor --- Multi-Layer Perceptron --- Random Forest --- Support Vector Machine --- agriculture --- drought --- NDVI --- MODIS --- landslide deformation --- InSAR --- reservoir water level --- Sentinel-1 --- Three Gorges Reservoir area (China) --- peri-urbanization --- urban growth boundary demarcation --- climate change --- climate migrants --- natural hazards --- flooding --- land use and land cover --- night-time light data --- Dhaka

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• Reference Manager
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Each year, natural hazards such as earthquakes, cyclones, flooding, landslides, wildfires, avalanches, volcanic eruption, extreme temperatures, storm surges, drought, etc., result in widespread loss of life, livelihood, and critical infrastructure globally. With the unprecedented growth of the human population, largescale development activities, and changes to the natural environment, the frequency and intensity of extreme natural events and consequent impacts are expected to increase in the future.Technological interventions provide essential provisions for the prevention and mitigation of natural hazards. The data obtained through remote sensing systems with varied spatial, spectral, and temporal resolutions particularly provide prospects for furthering knowledge on spatiotemporal patterns and forecasting of natural hazards. The collection of data using earth observation systems has been valuable for alleviating the adverse effects of natural hazards, especially with their near real-time capabilities for tracking extreme natural events. Remote sensing systems from different platforms also serve as an important decision-support tool for devising response strategies, coordinating rescue operations, and making damage and loss estimations.With these in mind, this book seeks original contributions to the advanced applications of remote sensing and geographic information systems (GIS) techniques in understanding various dimensions of natural hazards through new theory, data products, and robust approaches.

Research & information: general --- Geography --- sequential estimation --- InSAR time series --- groundwater --- land subsidence and rebound --- earthquake --- rapid mapping --- damage assessment --- deep learning --- convolutional neural networks --- ordinal regression --- aerial image --- landslide --- machine learning models --- remote sensing --- ensemble models --- validation --- ice storm --- forest ecosystems --- disaster impact --- post-disaster recovery --- ice jam --- snowmelt --- flood mapping --- monitoring and prediction --- VIIRS --- ABI --- NUAE --- flash flood --- BRT --- CART --- naive Bayes tree --- geohydrological model --- landslide susceptibility --- Bangladesh --- digital elevation model --- random forest --- modified frequency ratio --- logistic regression --- automatic landslide detection --- OBIA --- PBA --- random forests --- supervised classification --- landslides --- uncertainty --- K-Nearest Neighbor --- Multi-Layer Perceptron --- Random Forest --- Support Vector Machine --- agriculture --- drought --- NDVI --- MODIS --- landslide deformation --- InSAR --- reservoir water level --- Sentinel-1 --- Three Gorges Reservoir area (China) --- peri-urbanization --- urban growth boundary demarcation --- climate change --- climate migrants --- natural hazards --- flooding --- land use and land cover --- night-time light data --- Dhaka --- sequential estimation --- InSAR time series --- groundwater --- land subsidence and rebound --- earthquake --- rapid mapping --- damage assessment --- deep learning --- convolutional neural networks --- ordinal regression --- aerial image --- landslide --- machine learning models --- remote sensing --- ensemble models --- validation --- ice storm --- forest ecosystems --- disaster impact --- post-disaster recovery --- ice jam --- snowmelt --- flood mapping --- monitoring and prediction --- VIIRS --- ABI --- NUAE --- flash flood --- BRT --- CART --- naive Bayes tree --- geohydrological model --- landslide susceptibility --- Bangladesh --- digital elevation model --- random forest --- modified frequency ratio --- logistic regression --- automatic landslide detection --- OBIA --- PBA --- random forests --- supervised classification --- landslides --- uncertainty --- K-Nearest Neighbor --- Multi-Layer Perceptron --- Random Forest --- Support Vector Machine --- agriculture --- drought --- NDVI --- MODIS --- landslide deformation --- InSAR --- reservoir water level --- Sentinel-1 --- Three Gorges Reservoir area (China) --- peri-urbanization --- urban growth boundary demarcation --- climate change --- climate migrants --- natural hazards --- flooding --- land use and land cover --- night-time light data --- Dhaka

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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.

Research & information: general --- Geography --- 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 --- 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

Choose an application

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

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.

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