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Coastal environments are dynamic ecosystems, where erosion is influenced by meteorological/climatic, geological, biological, and anthropic factors. Erosion has worrying effects on the environment, infrastructure, lifelines, and buildings. Furthermore, climate change is exacerbating an already fragile situation. We are witnessing a high-risk situation and are convinced that this is the most appropriate time to focus on state-of-the-art remote sensing techniques for shoreline monitoring. The improvements in the spatial and spectral resolution of current and next generation satellite-based sensors and the significant progress in the spatial data processing identify remote sensing techniques that increase our knowledge of territory and coastline. This Special Issue aims to highlight an overview of all multiscale remote sensing techniques (e.g., high resolution images, photogrammetry, SAR, etc.) and a whole array of methods and techniques that process, analyse, and discuss multitemporal remotely sensed data. Thank you to all of our contributors and authors for their interesting and illuminating studies. Since this topic is complex and dynamic, we hope to develop this research with future works to form more cutting-edge studies.
History of engineering & technology --- DGPS measurements --- video camera observation --- shoreline position --- beach survey --- Sentinel-2 --- Remote Sensing --- habitat mapping --- mangroves --- coral reefs --- climate change --- vulnerable habitats --- side-scan sonar --- swath bathymetry --- habitat monitoring --- hurricane Sandy --- hurricane Joaquin --- shoreline detection --- remote sensing --- WorldView-2 --- Abruzzo --- multispectral classification --- shoreline --- coastline --- satellite images --- synthetic aperture radar (SAR) --- Sentinel-1 --- shoreline extraction --- coastline extraction --- active connection matrix (ACM) --- J-Net Dynamic --- edge detection --- canny edge detector --- coastline mapping --- geomatics --- SfM photogrammetry --- network RTK --- sea level rise --- coastlines --- 2100 --- storm surges --- heritage sites --- Pyrgi --- Mediterranean --- UAV --- DSM --- n/a
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Coastal environments are dynamic ecosystems, where erosion is influenced by meteorological/climatic, geological, biological, and anthropic factors. Erosion has worrying effects on the environment, infrastructure, lifelines, and buildings. Furthermore, climate change is exacerbating an already fragile situation. We are witnessing a high-risk situation and are convinced that this is the most appropriate time to focus on state-of-the-art remote sensing techniques for shoreline monitoring. The improvements in the spatial and spectral resolution of current and next generation satellite-based sensors and the significant progress in the spatial data processing identify remote sensing techniques that increase our knowledge of territory and coastline. This Special Issue aims to highlight an overview of all multiscale remote sensing techniques (e.g., high resolution images, photogrammetry, SAR, etc.) and a whole array of methods and techniques that process, analyse, and discuss multitemporal remotely sensed data. Thank you to all of our contributors and authors for their interesting and illuminating studies. Since this topic is complex and dynamic, we hope to develop this research with future works to form more cutting-edge studies.
DGPS measurements --- video camera observation --- shoreline position --- beach survey --- Sentinel-2 --- Remote Sensing --- habitat mapping --- mangroves --- coral reefs --- climate change --- vulnerable habitats --- side-scan sonar --- swath bathymetry --- habitat monitoring --- hurricane Sandy --- hurricane Joaquin --- shoreline detection --- remote sensing --- WorldView-2 --- Abruzzo --- multispectral classification --- shoreline --- coastline --- satellite images --- synthetic aperture radar (SAR) --- Sentinel-1 --- shoreline extraction --- coastline extraction --- active connection matrix (ACM) --- J-Net Dynamic --- edge detection --- canny edge detector --- coastline mapping --- geomatics --- SfM photogrammetry --- network RTK --- sea level rise --- coastlines --- 2100 --- storm surges --- heritage sites --- Pyrgi --- Mediterranean --- UAV --- DSM --- n/a
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Geomorphometry is the science of quantitative terrain characterization and analysis, and has traditionally focused on the investigation of terrestrial and planetary landscapes. However, applications of marine geomorphometry have now moved beyond the simple adoption of techniques developed for terrestrial studies, driven by the rise in the acquisition of high-resolution seafloor data and by the availability of user-friendly spatial analytical tools. Considering that the seafloor represents 71% of the surface of our planet, this is an important step towards understanding the Earth in its entirety.This volume is the first one dedicated to marine applications of geomorphometry. It showcases studies addressing the five steps of geomorphometry: sampling a surface (e.g., the seafloor), generating a Digital Terrain Model (DTM) from samples, preprocessing the DTM for subsequent analyses (e.g., correcting for errors and artifacts), deriving terrain attributes and/or extracting terrain features from the DTM, and using and explaining those terrain attributes and features in a given context. Throughout these studies, authors address a range of challenges and issues associated with applying geomorphometric techniques to the complex marine environment, including issues related to spatial scale, data quality, and linking seafloor topography with physical, geological, biological, and ecological processes. As marine geomorphometry becomes increasingly recognized as a sub-discipline of geomorphometry, this volume brings together a collection of research articles that reflect the types of studies that are helping to chart the course for the future of marine geomorphometry.
geomorphology --- simulation --- accuracy --- spatial scale --- marine geomorphology --- surface roughness --- forage fish --- satellite imagery --- thalwegs --- digital elevation models (DEMs) --- Seabed 2030 --- Pacific sand lance --- Acoustic applications --- python --- Nippon Foundation/GEBCO --- Oceanic Shoals Australian Marine Park --- submarine topography --- multi beam echosounder --- sedimentation --- bedforms --- carbonate banks --- polychaete --- cold-water coral --- multiscale --- automated-mapping --- semi-automated mapping --- sediment habitats --- Atlantic Ocean --- Northwestern Australia --- random forest --- benthic habitat mapping --- paleoclimate --- submerged glacial bedforms --- seafloor --- currents --- Cenomanian–Turonian --- Multibeam bathymetry --- geomorphometry --- ArcGIS --- filter --- seabed mapping --- coral reefs --- eastern Brazilian shelf --- digital terrain analysis --- multibeam spatial resolution --- multibeam --- multibeam sonar --- Timor Sea --- seafloor geomorphometry --- shelf-slope-rise --- terrain analysis --- seafloor mapping technologies --- spatial analysis --- Canary Basin --- paleobathymetry --- Bonaparte Basin --- pockmarks --- benthic habitats --- Malin Basin --- geographic object-based image analysis --- seafloor mapping standards and protocols --- GIS --- Bering Sea --- object segmentation --- Barents Sea --- bathymetry --- carbonate mound --- underwater acoustics --- integration artefacts --- multibeam echosounder --- domes --- global bathymetry --- Random Forests --- North Sea --- spatial prediction --- Glaciated Margin --- marine geology --- image segmentation --- shelf morphology --- Alaska --- paleoceanography --- confidence --- swath geometry --- volcanoes --- deglaciation --- Cretaceous --- DEM --- habitat mapping --- marine remote sensing --- reconstruction --- acoustic-seismic profiling --- canyons
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Coastal environments are dynamic ecosystems, where erosion is influenced by meteorological/climatic, geological, biological, and anthropic factors. Erosion has worrying effects on the environment, infrastructure, lifelines, and buildings. Furthermore, climate change is exacerbating an already fragile situation. We are witnessing a high-risk situation and are convinced that this is the most appropriate time to focus on state-of-the-art remote sensing techniques for shoreline monitoring. The improvements in the spatial and spectral resolution of current and next generation satellite-based sensors and the significant progress in the spatial data processing identify remote sensing techniques that increase our knowledge of territory and coastline. This Special Issue aims to highlight an overview of all multiscale remote sensing techniques (e.g., high resolution images, photogrammetry, SAR, etc.) and a whole array of methods and techniques that process, analyse, and discuss multitemporal remotely sensed data. Thank you to all of our contributors and authors for their interesting and illuminating studies. Since this topic is complex and dynamic, we hope to develop this research with future works to form more cutting-edge studies.
History of engineering & technology --- DGPS measurements --- video camera observation --- shoreline position --- beach survey --- Sentinel-2 --- Remote Sensing --- habitat mapping --- mangroves --- coral reefs --- climate change --- vulnerable habitats --- side-scan sonar --- swath bathymetry --- habitat monitoring --- hurricane Sandy --- hurricane Joaquin --- shoreline detection --- remote sensing --- WorldView-2 --- Abruzzo --- multispectral classification --- shoreline --- coastline --- satellite images --- synthetic aperture radar (SAR) --- Sentinel-1 --- shoreline extraction --- coastline extraction --- active connection matrix (ACM) --- J-Net Dynamic --- edge detection --- canny edge detector --- coastline mapping --- geomatics --- SfM photogrammetry --- network RTK --- sea level rise --- coastlines --- 2100 --- storm surges --- heritage sites --- Pyrgi --- Mediterranean --- UAV --- DSM --- DGPS measurements --- video camera observation --- shoreline position --- beach survey --- Sentinel-2 --- Remote Sensing --- habitat mapping --- mangroves --- coral reefs --- climate change --- vulnerable habitats --- side-scan sonar --- swath bathymetry --- habitat monitoring --- hurricane Sandy --- hurricane Joaquin --- shoreline detection --- remote sensing --- WorldView-2 --- Abruzzo --- multispectral classification --- shoreline --- coastline --- satellite images --- synthetic aperture radar (SAR) --- Sentinel-1 --- shoreline extraction --- coastline extraction --- active connection matrix (ACM) --- J-Net Dynamic --- edge detection --- canny edge detector --- coastline mapping --- geomatics --- SfM photogrammetry --- network RTK --- sea level rise --- coastlines --- 2100 --- storm surges --- heritage sites --- Pyrgi --- Mediterranean --- UAV --- DSM
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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
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
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