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Kartierung. --- Satellitenbild. --- Vergrößerung. --- Aerial photography --- Photographic interpretation. --- Photo-interprétation --- Technique. --- Podelta. --- Po River Delta (Italy)

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In this book are reported nine works related to land subsidence monitoring using remote sensing techniques. Land subsidence is a common phenomenon in many regions of the world, where it causes degradation of local ecosystems and disruption of economic activities. Its effects are more evident in densely populated areas in particular in low-lying territories such as river deltas and coastal areas where the combination of land subsidence and sea level rise increases the flooding risk. For this reason, the monitoring of ground deformations is a crucial step to obtain important information for the development of risk mitigation strategies. In the presented papers, the characteristics of land subsidence occurring in different study areas are described, and recent developments in the used methodologies for the monitoring of the ground displacements are discussed and validated also by means of ground-based data. Moreover, advantages and disadvantages of the adopted techniques are highlighted. The outcomes of these research works can provide national and local authorities with useful information for the implementation of integrated monitoring systems in the areas most affected by land subsidence.

land subsidence --- IPTA --- land-use --- water resource utilization --- groundwater change --- deformation --- geology --- Gävle --- InSAR --- PSI --- precise levelling --- sentinel-1 --- subsidence --- Sweden --- ALOS/PALSAR --- time series analysis --- SBAS --- hot spring water --- hydrothermal fluids --- Hakone Volcano --- satellite geodesy --- radar interferometry --- persistent scatterers --- distributed scatterers --- orbit combination --- Sentinel-1 --- cavern field --- salt deposit --- geophysical modeling --- underground gas storage --- GNSS --- ground movement --- subsidence monitoring --- integrated numerical simulation --- Dubrovnik --- satellite altimetry --- tide gauges --- vertical land motion --- DInSAR --- mining-induced tremors --- land surface deformation --- Upper Silesian Coal Basin --- Interferometry --- SNAP-StaMPS --- Ground deformation --- Po River Delta --- integrated monitoring --- time-series analysis --- n/a --- Gävle

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Coastal regions are susceptible to rapid changes, as they constitute the boundary between the land and the sea. The resilience of a particular segment of coast depends on many factors, including climate change, sea-level changes, natural and technological hazards, extraction of natural resources, population growth, and tourism. Recent research highlights the strong capabilities for remote sensing applications to monitor, inventory, and analyze the coastal environment. This book contains 12 high-quality and innovative scientific papers that explore, evaluate, and implement the use of remote sensing sensors within both natural and built coastal environments.

Research & information: general --- big data applications --- data processing --- data visualization --- neural networks --- reduction --- coastal waters --- urban expansion --- remote sensing and GIS --- expansion types and rates --- major explanatory factors --- Miami metropolitan area --- cliff coastlines --- cliff retreat --- time-series analysis --- airborne laser scanner --- warm upwelling --- sea surface temperature --- numerical modelling --- winter --- southern Baltic Sea --- beach monitoring --- mobile terrestrial LiDAR --- intensity calibration --- beach surface moisture --- Baltic coast --- Poland --- CORINE Land Cover --- land cover flow --- urbanisation --- afforestation --- deforestation --- spatial analysis --- SDGs --- coastal habitats --- ecosystem monitoring --- land cover mapping --- random forest algorithm --- Sentinel-2 --- modified soil-adjusted vegetation index 2-MSAVI2 --- normalized difference water index 2-NDWI2 --- brightness index 2-BI2 --- oil spill --- remote sensing --- review --- machine learning --- deep learning --- trajectory modeling --- vulnerability assessment --- coastal geomorphology --- shoreline change --- coastal process --- monitoring --- geomatic techniques --- Po River Delta --- archival multi-temporal data --- coastline changes --- emerged/submerged surfaces --- land subsidence --- relative sea level rise 2100 --- land cover --- dune coast --- air photograph --- South Baltic Sea --- coastal monitoring --- estuaries --- IoT --- lidar --- big data applications --- data processing --- data visualization --- neural networks --- reduction --- coastal waters --- urban expansion --- remote sensing and GIS --- expansion types and rates --- major explanatory factors --- Miami metropolitan area --- cliff coastlines --- cliff retreat --- time-series analysis --- airborne laser scanner --- warm upwelling --- sea surface temperature --- numerical modelling --- winter --- southern Baltic Sea --- beach monitoring --- mobile terrestrial LiDAR --- intensity calibration --- beach surface moisture --- Baltic coast --- Poland --- CORINE Land Cover --- land cover flow --- urbanisation --- afforestation --- deforestation --- spatial analysis --- SDGs --- coastal habitats --- ecosystem monitoring --- land cover mapping --- random forest algorithm --- Sentinel-2 --- modified soil-adjusted vegetation index 2-MSAVI2 --- normalized difference water index 2-NDWI2 --- brightness index 2-BI2 --- oil spill --- remote sensing --- review --- machine learning --- deep learning --- trajectory modeling --- vulnerability assessment --- coastal geomorphology --- shoreline change --- coastal process --- monitoring --- geomatic techniques --- Po River Delta --- archival multi-temporal data --- coastline changes --- emerged/submerged surfaces --- land subsidence --- relative sea level rise 2100 --- land cover --- dune coast --- air photograph --- South Baltic Sea --- coastal monitoring --- estuaries --- IoT --- lidar

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• Reference Manager
• EndNote
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Coastal regions are susceptible to rapid changes, as they constitute the boundary between the land and the sea. The resilience of a particular segment of coast depends on many factors, including climate change, sea-level changes, natural and technological hazards, extraction of natural resources, population growth, and tourism. Recent research highlights the strong capabilities for remote sensing applications to monitor, inventory, and analyze the coastal environment. This book contains 12 high-quality and innovative scientific papers that explore, evaluate, and implement the use of remote sensing sensors within both natural and built coastal environments.

big data applications --- data processing --- data visualization --- neural networks --- reduction --- coastal waters --- urban expansion --- remote sensing and GIS --- expansion types and rates --- major explanatory factors --- Miami metropolitan area --- cliff coastlines --- cliff retreat --- time-series analysis --- airborne laser scanner --- warm upwelling --- sea surface temperature --- numerical modelling --- winter --- southern Baltic Sea --- beach monitoring --- mobile terrestrial LiDAR --- intensity calibration --- beach surface moisture --- Baltic coast --- Poland --- CORINE Land Cover --- land cover flow --- urbanisation --- afforestation --- deforestation --- spatial analysis --- SDGs --- coastal habitats --- ecosystem monitoring --- land cover mapping --- random forest algorithm --- Sentinel-2 --- modified soil-adjusted vegetation index 2–MSAVI2 --- normalized difference water index 2–NDWI2 --- brightness index 2–BI2 --- oil spill --- remote sensing --- review --- machine learning --- deep learning --- trajectory modeling --- vulnerability assessment --- coastal geomorphology --- shoreline change --- coastal process --- monitoring --- geomatic techniques --- Po River Delta --- archival multi-temporal data --- coastline changes --- emerged/submerged surfaces --- land subsidence --- relative sea level rise 2100 --- land cover --- dune coast --- air photograph --- South Baltic Sea --- coastal monitoring --- estuaries --- IoT --- lidar --- n/a --- modified soil-adjusted vegetation index 2-MSAVI2 --- normalized difference water index 2-NDWI2 --- brightness index 2-BI2