0000000000849215

AUTHOR

Timothy S. Moore

showing 2 related works from this author

An optical classification tool for global lake waters

2017

Shallow and deep lakes receive and recycle organic and inorganic substances from within the confines of these lakes, their watershed and beyond. Hence, a large range in absorption and scattering and extreme differences in optical variability can be found between and within global lakes. This poses a challenge for atmospheric correction and bio-optical algorithms applied to optical remote sensing for water quality monitoring applications. To optimize these applications for the wide variety of lake optical conditions, we adapted a spectral classification scheme based on the concept of optical water types. The optical water types were defined through a cluster analysis of in situ hyperspectral…

Watershed010504 meteorology & atmospheric sciences0211 other engineering and technologiesAtmospheric correctionHyperspectral imagingSediment02 engineering and technology01 natural sciences6. Clean water/dk/atira/pure/sustainabledevelopmentgoals/life_below_waterColored dissolved organic matter13. Climate actionGeneral Earth and Planetary SciencesEnvironmental sciencemedia_common.cataloged_instancelakes; reflectance; classification; OWT; atmospheric correction; MERIS; OLCI; water quality14. Life underwaterWater qualitySDG 14 - Life Below WaterEuropean unionEutrophication021101 geological & geomatics engineering0105 earth and related environmental sciencesmedia_commonRemote sensing
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An optical water type framework for selecting and blending retrievals from bio-optical algorithms in lakes and coastal waters.

2014

Bio-optical models are based on relationships between the spectral remote sensing reflectance and optical properties of in-water constituents. The wavelength range where this information can be exploited changes depending on the water characteristics. In low chlorophyll-a waters, the blue/green region of the spectrum is more sensitive to changes in chlorophyll-a concentration, whereas the red/NIR region becomes more important in turbid and/or eutrophic waters. In this work we present an approach to manage the shift from blue/green ratios to red/NIR-based chlorophyll-a algorithms for optically complex waters. Based on a combined in situ data set of coastal and inland waters, measures of over…

Bio opticalWavelength rangeRemote sensing reflectanceSoil ScienceGeologyArticleData setApproximation errorOcean colorEnvironmental scienceComputers in Earth SciencesRoot-mean-square deviationAlgorithmRemote sensingRemote sensing of environment
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