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An Optical Water Type Classification Scheme for Hyperspectral Remote Sensing Reflectance: A Case Study in Lake Erie

https://doi.org/10.2139/ssrn.4762419
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Agencies Collaborate, Develop a Cyanobacteria Assessment Network
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Classification of Inland Waters Based on Bio-Optical Properties
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Unmixing of Pollution-Associated Sea Snot in the Near Surface After Its Outbreak in the Sea of Marmara Using Hyperspectral PRISMA Data
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Feature Selection for Classification of Hyperspectral Data by SVM
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The Hughes phenomenon in hyperspectral classification based on the ground spectrum of grasslands in the region around Qinghai Lake
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Comparison of N,N-Dimethylformamide, Dimethyl Sulfoxide, and Acetone for Extraction of Phytoplankton Chlorophyll
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Hyperspectral temperature and salt dependencies of absorption by water and heavy water in the 400-750 nm spectral range
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Chlorophyll-based model underpinned by measured inherent optical properties of Jerlov water types
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Using Machine Learning for Timely Estimates of Ocean Color Information From Hyperspectral Satellite Measurements in the Presence of Clouds, Aerosols, and Sunglint
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A Universal Fuzzy Logic Optical Water Type Scheme for the Global Oceans
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Optimization of Landsat Chl-a Retrieval Algorithms in Freshwater Lakes through Classification of Optical Water Types
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Analysis of variations in ocean color1
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Remote sensing of the cyanobacterial pigment phycocyanin in turbid inland water
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Routine monitoring of western Lake Erie to track water quality changes associated with cyanobacterial harmful algal blooms
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Using empirical orthogonal functions derived from remote-sensing reflectance for the prediction of phytoplankton pigment concentrations
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