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Series

2018

Chlorophyll-a

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

Developing Ocean Color Algorithm Using Moderate Resolution Imaging Spectroradiometer (Modis) Sensor For Shallow Coastal Water Bodies, Mohd Manzar Abbas Jun 2018

Developing Ocean Color Algorithm Using Moderate Resolution Imaging Spectroradiometer (Modis) Sensor For Shallow Coastal Water Bodies, Mohd Manzar Abbas

FIU Electronic Theses and Dissertations

This study analyses the spatial and temporal variability of chlorophyll-a in Chesapeake Bay; assesses the performance of Ocean Color 3M (OC3M) algorithm; and develops a novel algorithm to estimate chlorophyll-a for coastal shallow water. The OC3M algorithm yields an accurate estimate of chlorophyll-a concentration for deep ocean water (RMSE=0.016), but it failed to perform well in the coastal water system (RMSE=23.17) of Chesapeake Bay. A novel algorithm was developed which utilizes green and red bands of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The novel algorithm derived the chlorophyll-a concentration more accurately in Chesapeake Bay (RMSE=4.20) than the OC3M algorithm. …

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An Assessment Of Atmospheric And Meteorological Factors Regulating Red Sea Phytoplankton Growth, Wenzhao Li, Hesham El-Askary, Mohamed A. Qurban, Emmanouil Proestakis, Michael J. Garay, Olga V. Kalishnikova, Vassilis Amiridis, Antonis Gkikas, Eleni Marinou, Thomas Piechota, K. P. Manikandan Apr 2018

An Assessment Of Atmospheric And Meteorological Factors Regulating Red Sea Phytoplankton Growth, Wenzhao Li, Hesham El-Askary, Mohamed A. Qurban, Emmanouil Proestakis, Michael J. Garay, Olga V. Kalishnikova, Vassilis Amiridis, Antonis Gkikas, Eleni Marinou, Thomas Piechota, K. P. Manikandan

Mathematics, Physics, and Computer Science Faculty Articles and Research

This study considers the various factors that regulate nutrients supply in the Red Sea. Multi-sensor observation and reanalysis datasets are used to examine the relationships among dust deposition, sea surface temperature (SST), and wind speed, as they may contribute to anomalous phytoplankton blooms, through time-series and correlation analyses. A positive correlation was found at 0–3 months lag between chlorophyll-a (Chl-a) anomalies and dust anomalies over the Red Sea regions. Dust deposition process was further examined with dust aerosols’ vertical distribution using satellite lidar data. Conversely, a negative correlation was found at 0–3 months lag between SST anomalies …

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