Remote Sensing Applications in Ocean Observation

doi:10.3390/books978-3-0365-6439-5

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Remote Sensing Applications in Ocean Observation

Edited by

January 2023

610 pages

ISBN978-3-0365-6438-8 (Hardback)
ISBN978-3-0365-6439-5 (PDF)

https://doi.org/10.3390/books978-3-0365-6439-5

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This book is a reprint of the Special Issue Remote Sensing Applications in Ocean Observation that was published in

Engineering

Environmental & Earth Sciences

Summary

Since the launch of Seasat, TIROS-N, and Nimbus-7 satellites equipped with ocean observation sensors in 1978, a new era of ocean remote sensing has opened. Today, remotely sensed data have been widely used in oceanographic studies. This reprint collects various advanced ocean remote sensing technologies and their applications, including the use of artificial intelligence techniques to explore ocean information and bibliometric analysis to assess researchers and trends in this scientific field. The observations of various sensors enrich the application of ocean environment monitoring and ocean dynamical analysis. If you are interested in understanding the application of ocean remote sensing, this monograph should be very helpful.

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Keywords

bibliometric analysis; remote sensing; oil slicks; oil detection; coastal waters of Myanmar; upwelling; monsoon; remote equatorial forcing; coastal upwelling; Himawari-8; sea surface temperature; Taiwan; topographic position index; upwelling index; mapping; satellite remote sensing; quantitative mapping; spatial analysis; the East Australian Current; New South Wales; coastal upwelling; shelf circulation; seagrass; Zostera marina L.; remote sensing; reclamation; spatial and temporal changes; mesoscale eddies; the Indonesian Seas; sea level anomaly; nonlinearity; barotropic instability; baroclinic instability; SAR; CNN; Sentinel-1; ship detection; geostationary ocean color imager (GOCI); GDPS; SeaDAS; normalized water-leaving radiance; atmospheric correction; fish assemblage; temperature; environmental change; Yellow Sea coastal current; East China Sea; lidar; remote sensing sensors; backward scattering intensity; ocean Scheimpflug lidar; volume scattering function; Arabian Gulf; Gulf of Oman; MODIS; algal blooms; chlorophyll-a; SST; bathymetry; semidiurnal internal tides; the Sulu-Sulawesi Seas; sea surface height; plane wave fit method; energy flux; Kuroshio intrusion; Kuroshio Current Loop; cold-core anticyclonic eddy; cloud masking; turbid water; remote sensing; spectral variability; total suspended sediment; chlorophyll-a bloom; typhoon; South China Sea; alongshore current; marine heatwaves; sea surface temperatures; summer 2021; northwestern Pacific Ocean; westerly jet; North Pacific Subtropical High; ocean color; water type taxonomies; trophic state; inherent optical properties; Forel-Ule Scale; Sargassum; atmospheric correction; aerosols; OLCI; Daya Bay Nuclear Power Plants; thermal discharge; long-term changes; Landsat; radiative transfer equation; split-window algorithm; power plant installed capacity; flood tide; ebb tide; wind field; SST; bias correction; deep learning; ConvLSTM; 3D-C BAM; Kuroshio branch; salinity; chlorophyll-a; North Pacific subtropical gyre; satellite observation; in situ observation; Taiwan Strait; flow pattern; high-frequency radar; drifter; tide; turbulent mixing; upper ocean response; Super Typhoon Goni; satellite observations; sea surface temperature; HYCOM reanalysis results; internal tides; spatiotemporal variation; East China Sea; modal structure; energy cascade; machine learning; ocean subsurface salinity structure; South China Sea; satellite remote sensing data; oil slicks; data fusion; offshore detection; SAR images; meteorological data; deep learning; AI explanation; sea ice; Bayesian algorithm; CFOSAT; scatterometer; SAR; internal solitary waves; turbulence; Yellow Sea; wake detection; radiation sensitivity; noise equivalent reflectance difference; three-dimensional eddy reconstruction; loop current rings; gulf of Mexico; gravest empirical modes; n/a