Remote Sensing in Coastline Detection

• Autore: Dominici Donatella
• Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
• Descrizione fisica: 1 electronic resource (138 p.)
• Soggetto topico: History of engineering & technology
• Soggetto non controllato: 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
• Persona (resp. second.): DominiciDonatella
• Sommario/riassunto: 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.
• Titolo autorizzato: Remote Sensing in Coastline Detection
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557546503321
• Lo trovi qui: Univ. Federico II