S
Sachidananda Mishra
Researcher at National Oceanic and Atmospheric Administration
Publications - 26
Citations - 1026
Sachidananda Mishra is an academic researcher from National Oceanic and Atmospheric Administration. The author has contributed to research in topics: Hyperspectral imaging & Environmental science. The author has an hindex of 10, co-authored 21 publications receiving 731 citations. Previous affiliations of Sachidananda Mishra include Mississippi State University & Dow AgroSciences.
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Normalized difference chlorophyll index: A novel model for remote estimation of chlorophyll-a concentration in turbid productive waters
TL;DR: In this paper, a normalized difference chlorophyll index (NDCI) was proposed to predict chl-a (chl- a ) concentration from remote sensing data in estuarine and coastal turbid productive waters.
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Quantifying cyanobacterial phycocyanin concentration in turbid productive waters: A quasi-analytical approach
TL;DR: In this article, a multi-band quasi analytical algorithm was used to determine phytoplankton absorption coefficients, a ϕ (λ ), from above surface remote sensing reflectance, R rs (λ ).
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Post-spill state of the marsh: Remote estimation of the ecological impact of the Gulf of Mexico oil spill on Louisiana Salt Marshes
Deepak R. Mishra,Hyun Jung Cho,Shuvankar Ghosh,Amelia A. A. Fox,Christopher Downs,Paul B.T. Merani,Philemon Kirui,Nick Jackson,Sachidananda Mishra +8 more
TL;DR: In this paper, the authors presented the first quantitative assessment on the ecological impact of the spill on the salt marsh habitats along the southeastern Louisiana (LA) coast, using satellite and ground data.
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A Novel Algorithm for Predicting Phycocyanin Concentrations in Cyanobacteria: A Proximal Hyperspectral Remote Sensing Approach
TL;DR: It is found that the existing band ratio algorithms are highly sensitive to chlorophylls, making them inaccurate in predicting cyanobacterial abundance in the presence of other chlorophylla-containing organisms.
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Bio-Optical Inversion in Highly Turbid and Cyanobacteria-Dominated Waters
TL;DR: A quasi-analytical algorithm has been parameterized using in situ data to retrieve inherent optical properties from Rrs(λ) in highly turbid productive aquaculture ponds, where the phytoplankton absorption coefficient contributes 54 % of the total absorption at 443 nm.