Estimation of Cyanobacterial Pigments in a Freshwater Lake using OCM Satellite Data

Padmanava Dash, Nan D. Walker, Deepak R. Mishra, Chuanmin Hu, James L. Pinckney, Eurico J. D’Sa

Research output: Contribution to journalArticlepeer-review

Abstract

<p> <p id="x-x-sp0095"> Cyanobacteria represent a major harmful algal group in fresh to brackish water environments. Lac des Allemands, a freshwater lake of 49 km2 southwest of New Orleans, Louisiana on the upper end of the Barataria <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/estuary" title="Learn more about Estuary from ScienceDirect's AI-generated Topic Pages"> Estuary </a> , provides a natural laboratory for remote characterization of cyanobacterial blooms because of their seasonal occurrence. The Oceansat-1 <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/extraterrestrial-ocean" title="Learn more about Extraterrestrial Ocean from ScienceDirect's AI-generated Topic Pages"> satellite Ocean </a> Colour Monitor (OCM) provides measurements similar to <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/sea-viewing-wide-field-of-view-sensor" title="Learn more about Sea-Viewing Wide Field-of-View Sensor from ScienceDirect's AI-generated Topic Pages"> SeaWiFS </a> but with <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/high-spatial-resolution" title="Learn more about High Spatial Resolution from ScienceDirect's AI-generated Topic Pages"> higher spatial resolution </a> , and this work is the first attempt to use OCM measurements to quantify cyanobacterial pigments. The satellite signal was first vicariously calibrated using SeaWiFS as a reference, and then corrected to remove the atmospheric effects using a customized atmospheric correction procedure. Then, empirical inversion algorithms were developed to convert the OCM <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/remote-sensing" title="Learn more about Remote Sensing from ScienceDirect's AI-generated Topic Pages"> remote sensing </a> reflectance ( <em> R </em> <em> rs </em> ) at bands 4 and 5 (centered at 510.6 and 556.4 nm, respectively) to concentrations of phycocyanin (PC), the primary cyanobacterial pigment. A holistic approach was used to minimize the influence of other optically active constituents on the PC algorithm. Similarly, empirical algorithms to estimate chlorophyll <em> a </em> (Chl <em> a </em> ) concentrations were developed using OCM bands 5 and 6 (centered at 556.4 and 669 nm, respectively). The best PC algorithm (R <sup> 2 </sup> = 0.7450, p &lt; 0.0001, n = 72) yielded a <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/root-mean-square-error" title="Learn more about Root-Mean-Square Error from ScienceDirect's AI-generated Topic Pages"> root mean square error </a> (RMSE) of 36.92 &mu;g/L with a relative RMSE of 10.27% (PC from 2.75 to 363.50 &mu;g/L, n = 48). The best algorithm for Chl <em> a </em> (R <sup> 2 </sup> = 0.7510, p &lt; 0.0001, n = 72) produced an RMSE of 31.19 &mu;g/L with a relative RMSE of 16.56% (Chl <em> a </em> from 9.46 to 212.76 &mu;g/L, n = 48). While more field data are required to further validate the long-term performance of these algorithms, currently they represent the best protocol for establishing a long time-series of cyanobacterial blooms in the Lac des Allemands using OCM data. </p></p>
Original languageAmerican English
JournalRemote Sensing of Environment
Volume115
DOIs
StatePublished - Dec 1 2011

Keywords

  • OCM
  • Oceansat-1
  • Remote sensing
  • Cyanobacteria
  • Phycocyanin
  • PC
  • Chlorophyll a
  • Chl a
  • Atmospheric correction
  • Vicarious calibration

Disciplines

  • Life Sciences

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