Coastal Waters Monitoring Using Remote Sensing Technology
Around 10% of the global population lives in the world’s coastal zones, mostly concentrated in the world’s largest megacities. In many regions, the population is exposed to a variety of natural hazards and space-based observations. This Special Issue will focus on the usage of remote sensing alone o...
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|---|---|
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| Year of Publication: | 2022 |
| Language: | English |
| Physical Description: | 1 electronic resource (498 p.) |
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| 245 | 1 | 0 | |a Coastal Waters Monitoring Using Remote Sensing Technology |
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| 300 | |a 1 electronic resource (498 p.) | ||
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| 520 | |a Around 10% of the global population lives in the world’s coastal zones, mostly concentrated in the world’s largest megacities. In many regions, the population is exposed to a variety of natural hazards and space-based observations. This Special Issue will focus on the usage of remote sensing alone or in synergy with in situ measurments and modeling tools to provide precise and systematic information about processes acting in the world’s coastal zones. | ||
| 546 | |a English | ||
| 650 | 7 | |a Research & information: general |2 bicssc | |
| 653 | |a ACOLITE | ||
| 653 | |a coastal waters | ||
| 653 | |a atmospheric correction | ||
| 653 | |a time-series | ||
| 653 | |a management | ||
| 653 | |a Sentinel-2 | ||
| 653 | |a radon transform | ||
| 653 | |a remote sensing | ||
| 653 | |a bathymetry inversion | ||
| 653 | |a multi-scale monitoring | ||
| 653 | |a image augmentation | ||
| 653 | |a phytoplankton remote sensing | ||
| 653 | |a coastal ocean | ||
| 653 | |a red tides | ||
| 653 | |a black pixel assumption | ||
| 653 | |a satellite | ||
| 653 | |a sediment transport | ||
| 653 | |a coastal geomorphology | ||
| 653 | |a ocean color | ||
| 653 | |a GOCI | ||
| 653 | |a VIIRS | ||
| 653 | |a turbid waters | ||
| 653 | |a satellite-derived bathymetry | ||
| 653 | |a Copernicus programme | ||
| 653 | |a multi-temporal approach | ||
| 653 | |a lidar | ||
| 653 | |a turbidity | ||
| 653 | |a coastal upwelling | ||
| 653 | |a wind forcing | ||
| 653 | |a river plume | ||
| 653 | |a MODIS | ||
| 653 | |a Arctic Ocean | ||
| 653 | |a hurricanes | ||
| 653 | |a water quality | ||
| 653 | |a Puerto Rico | ||
| 653 | |a harmful algal blooms | ||
| 653 | |a Chattonella spp. | ||
| 653 | |a Skeletonema spp. | ||
| 653 | |a backscattering | ||
| 653 | |a Ariake Sea | ||
| 653 | |a chlorophyll-a variability | ||
| 653 | |a spring–neap tides | ||
| 653 | |a MODIS-Aqua | ||
| 653 | |a total suspended sediment | ||
| 653 | |a river discharge | ||
| 653 | |a band registration | ||
| 653 | |a morphological registration | ||
| 653 | |a multispectral camera | ||
| 653 | |a Micasense Rededge-M | ||
| 653 | |a Pearl River estuary | ||
| 653 | |a diffuse attenuation coefficient | ||
| 653 | |a S-EOF | ||
| 653 | |a land subsidence | ||
| 653 | |a multi-temporal SAR interferometry | ||
| 653 | |a sea-surface height | ||
| 653 | |a relative sea level change | ||
| 653 | |a satellite altimetry data | ||
| 653 | |a GNSS | ||
| 653 | |a coastal urban centers | ||
| 653 | |a natural protected areas | ||
| 653 | |a climate change impact | ||
| 653 | |a physics-based inversion method | ||
| 653 | |a ocean surface circulation | ||
| 653 | |a high frequency radar | ||
| 653 | |a self-organizing map | ||
| 653 | |a empirical orthogonal function | ||
| 653 | |a neural networks | ||
| 653 | |a synoptic characteristics | ||
| 653 | |a wave radar | ||
| 653 | |a sea waves | ||
| 653 | |a model data | ||
| 653 | |a Mediterranean sea | ||
| 653 | |a small river plume | ||
| 653 | |a aerial drone | ||
| 653 | |a coastal processes | ||
| 653 | |a frontal zones | ||
| 653 | |a internal waves | ||
| 653 | |a along-track interferometric synthetic aperture radar (ATI-SAR) | ||
| 653 | |a current line-of-sight (LOS) velocity | ||
| 653 | |a azimuth ambiguity | ||
| 653 | |a baseline-to-platform speed ratio estimation | ||
| 653 | |a storm surge | ||
| 653 | |a coastal flooding | ||
| 653 | |a marine storms | ||
| 653 | |a natural hazards | ||
| 653 | |a steric-effect | ||
| 653 | |a satellite altimetry | ||
| 653 | |a ADG/CDOM colored dissolved organic matter | ||
| 653 | |a Sentinel 3 | ||
| 653 | |a southwestern Puerto Rico | ||
| 653 | |a ocean tidal backwater | ||
| 653 | |a stage–discharge relation | ||
| 653 | |a ocean tide model | ||
| 653 | |a Mekong Delta | ||
| 653 | |a suspended particulate matter | ||
| 653 | |a ocean color data | ||
| 653 | |a satellite remote sensing | ||
| 653 | |a in situ measurements | ||
| 653 | |a C2RCC | ||
| 653 | |a Landsat-8 OLI | ||
| 653 | |a Sentinel-2 MSI | ||
| 653 | |a Mzymta River | ||
| 653 | |a Black Sea | ||
| 653 | |a MUR SST | ||
| 653 | |a SST fronts | ||
| 653 | |a Inner Sea of Chiloé | ||
| 653 | |a northern Patagonia | ||
| 653 | |a suspended sediment | ||
| 653 | |a Typhoon Soudelor | ||
| 653 | |a spatial–temporal distribution | ||
| 653 | |a HF marine radars | ||
| 653 | |a wave energy | ||
| 776 | |z 3-0365-1233-0 | ||
| 700 | 1 | |a Benveniste, Jérôme |4 edt | |
| 700 | 1 | |a Vignudelli, Stefano |4 oth | |
| 700 | 1 | |a Benveniste, Jérôme |4 oth | |
| 906 | |a BOOK | ||
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