Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 26 for “"ocean color"”.
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Ocean color modeling: Parameterization and interpretation
<p>The ocean color as observed near the water surface is determined mainly by dissolved and particulate substances, known as "optically-active constituents," in the upper water column. The goal of ocean color modeling is to interpret an ocean color spectrum quantitatively to estimate the suite of …
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Computational approaches for sub-meter ocean color remote sensing
The satellite ocean color remote sensing paradigm developed by government space agencies enables the assessment of ocean color products on global scales at kilometer resolutions. A similar paradigm has not yet been developed for regional scales at sub-meter resolutions, but it is essential for …
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Nanosatellite Hyperspectral Imaging Performance Modeling for Ocean Color Detection.
Earth’s oceans are an integral sub-system of our planet, an invaluable resource, and an informative proxy for understanding human-related climate impact. Ocean color observations are particularly useful for monitoring and modeling phytoplankton, valuable fauna that form the basis of the marine food …
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Scale closure in upper ocean optical properties : from single particles to ocean color
… of chlorophyll concentration from satellite ocean color are an indicator of phytoplankton primary productivity, with implications for foodweb structure, fisheries, and the global carbon cycle. Current models describing the relationship between optical properties and chlorophyll do not account …
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Scale closure in upper ocean optical properties : from single particles to ocean color
… of chlorophyll concentration from satellite ocean color are an indicator of phytoplankton primary productivity, with implications for foodweb structure, fisheries, and the global carbon cycle. Current models describing the relationship between optical properties and chlorophyll do not account …
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Spatio-Temporal Dynamics Of Phytoplankton Biomass From Ocean Color Remote Sensing And Cmip5 Model Suites
… advancing fast through developments of multiple ocean-color remote sensing algorithms and via developments in ecological modules incorporated in climate models. While climate models are projecting relatively clear trends in ocean ecology over the next century, distinguishing between interannual …
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Ecosystem health in Guánica Bay and La Parguera, Puerto Rico: Remote sensing of ocean color and metal analysis of coral tissue and surficial sediments
… (XRF) and Direct Mercury Analyzer (DMA- 80). Ocean color remote sensing was used to estimate nutrient inputs and phytoplankton biomass through chlorophyll-<em>a </em>(chl-a) concentrations from Guánica Bay to La Parguera. Chl-a is an indicator of the abundance of phytoplankton and biomass in …
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Submesoscale Biophysical Interactions on the Gulf Stream: Eddies, Fronts, and New Observational Methods
<p>Our oceans are a key part of the Earth system, an underappreciated bastion of our carbon cycle, and the home of incredible biodiversity, yet marine ecosystems are extremely challenging to model with a range of feedbacks that are not understood. Particularly poorly understood are linkages between …
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Exploration of Biophysical Interactions Associated with Mesoscale Variability in the Central Gulf of Mexico
… Validation, and Interpretation of Satellite Oceanographic data (AVISO). Biological characteristics of the GMx have been recognized as ocean color identified by the satellites SeaWiFS and MODISA. A climatology data set and a chlorophyll anomaly (CLa) was made using the 14-year mean determined …
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Satellite indices of fluvial influence in coastal waters
… between time series of riverine discharge and an ocean color satellite-derived property in the region proximal to a river's discharge point.</p><p>These indices are employed to map the seasonal spatio-temporal variability of the Mississippi's sediment plume in the presence of discharge and wind …
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Observations from working with a simple mathematical model of light absorption by small particles in the ocean
In order to investigate the possibility of using oceanic visual spectrum data (i.e., ocean color) to differentiate between phytoplankton cell types, a simple mathematical model of light absorption was constructed in MATLAB, in order to investigate the effects of depth, cell size, and water on light …
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The Observation, Modeling, and Retrieval of Bio-Optical Properties for Coastal Waters of the Southern Chesapeake Bay
… are the dominant contributors to IOPs of oceanic Case 1 waters, colored dissolved organic matter (CDOM) derived from non-phytoplankton sources and sedimentary particles also play very important roles in coastal Case 2 waters. Strongly influenced by riverine discharge, the shallow coastal …
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The Influence of Changing Nutrients and Warming on Phytoplankton and its Interactions with Zooplankton in the North Sea
… long-term satellite and in situ data. Satellite ocean-color analyses show predominantly declining Chl-a anomalies across the German Bight, with localized increases near the Elbe estuary. SST explains part of the long-term Chl-a variability, but responses differ strongly in space. In situ analyses …
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Development of bio-optical algorithms to estimate chlorophyll in the Great Salt Lake and New England lakes using in situ hyperspectral measurements
… band combinations were examined for both ocean color chlorophyll (OC) and maximum chlorophyll index (MCI) algorithms. A simulated 709 nm band was created for MODIS using the 754 nm band, providing a method for testing MODIS with algorithms relying on the key 705 nm to 715 nm wavelength …
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From Hyperspectral Indices to Global Fluorescence: PACE Vegetation Indices as Predictors of Terrestrial Photosynthesis
… data gaps. The NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission presents an opportunity to overcome these challenges through its hyperspectral Ocean Color Instrument and globally distributed Land Vegetation Index (LANDVI) product suite. This study's primary contribution lies in …
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Application of Machine Learning Techniques to Forecast Harmful Algal Blooms in Gulf of Mexico
… sake of simplicity of our application we assume ocean color satellite imagery from the National Oceanic and Atmospheric Administration as a proxy for HABs.</p> <p>In this study we use a deep neural network trained on the 2-Dimensional time series proxy data to provide a forecast of the HABs’ …
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Physical Control of Biological Processes in the Central Equatorial Pacific: A Data Assimilative Modeling Study
… <p>When actual EqPac cruise data and SeaWiFS ocean color data are assimilated, one can objectively determine whether or not a given model structure is consistent with specific sets of observations. For instance, a brief period of macro-nutrient limitation during the 1997–98 El Niño, as well as …
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Utility of remote sensing data in retrieval of water quality consituents concentrations in coastal water of New Jersey
… are the concentrations of chlorophyll (CHL), color dissolved organic matter (CDOM) and total suspended materials (TSM). Ocean color remote sensing, a technique to collect color data by detection of upward radiance from a distance (Bukata et al.,1995), provides a synoptic view for determining …
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Oceanic Light Absorption Properties: Assessment and Characterization in the Southeastern Bering Sea Using Field and Satellite Observations
… of optically active components (such as colored dissolved organic matter, non-algal particulate matter, and phytoplankton) from ocean color remote sensors has been the lack of in-situ bio-optical data in the Bering Sea. To address this issue, the central part of this dissertation was to …
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Employment of Multi-Source Satellite-Based Observations in Air Quality Modeling over Asia
… Himawari Imager (AHI), and Geostationary Ocean Color Imager (GOCI). While the model initially underestimated AOD by -50.73% in 2019, the emissions updates, with increases in NOx and primary PM emissions by 122.79% and 114.63%, reduced the negative bias to -33.84% and -19.60%, respectively. …
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