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Rakesh Kumar Singh

Researcher at Indian Institute of Technology Madras

Publications -  10
Citations -  158

Rakesh Kumar Singh is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Radiance & Atmospheric correction. The author has an hindex of 5, co-authored 10 publications receiving 116 citations.

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A novel method for estimation of aerosol radiance and its extrapolation in the atmospheric correction of satellite data over optically complex oceanic waters

TL;DR: In this paper, the Rayleigh-corrected radiance at 748 nm, after correcting the influence of the elevated radiance contributed by suspended sediments and algal blooms, is employed in the present method to estimate aerosol radiance in a MODIS-Aqua band centered at 531nm.
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Classification of algal bloom species from remote sensing data using an extreme gradient boosted decision tree model

TL;DR: Coastal and open ocean regions throughout the world are now subject to an array of toxic, harmful, or more intense algal blooms with an increasing trend of incidence over large geographical areas as discussed by the authors.
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A Multidisciplinary Remote Sensing Ocean Color Sensor: Analysis of User Needs and Recommendations for Future Developments

TL;DR: With these new capabilities and key design features, it will become feasible to resolve ocean color signals under most environmental circumstances and answer science questions related to changing conditions in the coastal and marine ecosystems and biogeochemical cycles due to climate change.
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A modern robust approach to remotely estimate chlorophyll in coastal and inland zones

TL;DR: In this article, a robust algorithm (Generalized ABI, GABI algorithm) was proposed for chlorophyll concentration retrieval based on Algal Bloom index (ABI) which separates phytoplankton signals from other constituents in the water column.
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UV-NIR approach with non-zero water-leaving radiance approximation for atmospheric correction of satellite imagery in inland and coastal zones.

TL;DR: The highest accuracy and consistency of the UVNIR-ex algorithm indicates that it is more suited for estimating the aerosol optical properties and water-leaving radiance and has a significant advantage over the requirement of shortwave infrared bands for turbid and productive waters.