Gustavo A. Carvalho, G. ., University of Miami - RSMAS/MP, Miami, USA, gcarvalho@rsmas.miami.edu
Peter J. Minnett, P. ., University of Miami - RSMAS/MPO, Miami, USA,
Warner Baringer , W. ., University of Miami - RSMAS/MPO, Miami, USA,
Viva Banzon, V. ., University of Miami - RSMAS/MPO, Miami, USA,

SPATIAL AND TEMPORAL VARIABILITY OF THREE DISTINCT SATELLITE OCEAN COLOR ALGORITHMS TO IDENTIFY HARMFUL ALGAL BLOOMS OFF THE WEST FLORIDA COAST

Near real-time remote sensing imagery has been widely used to identify ocean surface features such as oil slicks, eddies, upwelling, river plumes and harmful algal blooms (HABs). Since toxic blooms of Karenia brevis are observed yearly in the west Florida coast, an accurate technique to remotely detect HABs is highly desired. A NOAA monitoring system identifies areas likely to be classified as HABs, but field samples are still required for confirmation. Two other recent approaches, also based on visible space-borne measurements, have shown promising results for HABs’ detection. The spatial and temporal variability of these three techniques’ products are examined to address two questions: 1) How effectively are HABs’ detected along the entire shoreline, from Key West to Cape San Blass; and 2) Are these algorithms successful year-round? The predictive success of these three satellite-based methodologies is evaluated by comparing with an in situ database of cell counts. Quantifying the uncertainties associated with these algorithms is important to provide guidance for resource management decisions to better plan mitigation actions.

Oral presentation

Presentation is given by student: Yes
Session #:120
Date: 03-03-2008
Time: 17:00