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Proceedings Paper

Satellite estimates of chlorophyll-a concentration in the Brazilian southeastern continental shelf and slope waters, southwestern Atlantic
Author(s): Milton Kampel; Salvador A. Gaeta; João A. Lorenzzetti; Mayza Pompeu
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Paper Abstract

Comparisons between in situ measurements of surface chlorophyll-a concentration (CHL) and ocean color remote sensing estimates were conducted in the Brazilian Southeast coast, Southwestern South Atlantic. In situ fluorometric data were acquired in four hydrographic cruises carried out during the austral summer and winter of 2001 and 2002. The satellite estimates of CHL were derived from SeaWiFS data recorded in HRPT mode by INPE's station with a nominal 1.1 km resolution. Four algorithms were used to estimate CHL: two empirical - Ocean Chlorophyll 4 bands (OC4v4), and 2 bands (OC2v4); one semi-analytical - Garver, Siegel, Maritorena (GSM01); and one based on neural network (NN). Comparisons of estimated and measured CHL were done within a temporal window of 12 hours from the in situ sampling time. SeaWiFS algorithms values are 5x5 pixel medians centered on the location of in situ sampling station. For the study area CHL was fairly well estimated by all the SeaWiFS algorithms. OC4 performed better (R2 = 0.71; rms = 0.22) than the other algorithms (OC2, GSM01, and NN). The OC2 algorithm also showed a good performance with R2 = 0.67 and rms = 0.23. The neural network algorithm performed better than the semi-analytical one (R2 = 0.62 and 0.55, respectively), but with a higher rms (0.34 and 0.20, respectively). In general, the OC4, OC2, and NN algorithms showed a tendency for overestimating CHL at higher concentrations and underestimating at lower values. The semi-analytic GSM01 algorithm overestimated only the lower CHL, but underestimated most of the other values.

Paper Details

Date Published: 5 October 2007
PDF: 7 pages
Proc. SPIE 6680, Coastal Ocean Remote Sensing, 668012 (5 October 2007); doi: 10.1117/12.736647
Show Author Affiliations
Milton Kampel, Instituto Nacional de Pesquisas Espaciais (Brazil)
Salvador A. Gaeta, Univ. de São Paulo (Brazil)
João A. Lorenzzetti, Instituto Nacional de Pesquisas Espaciais (Brazil)
Mayza Pompeu, Univ. de São Paulo (Brazil)


Published in SPIE Proceedings Vol. 6680:
Coastal Ocean Remote Sensing
Robert J. Frouin; ZhongPing Lee, Editor(s)

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