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Um algoritmo empírico regional para estimativa de clorofila-a na plataforma continental adjacente à Baixada Santista foi desenvolvido a partir de dados radiométricos e de concentração de clorofila-a, obtidos em 49 estações oceanográficas durante dois cruzeiros, em outubro de 2005 e março de 2006. Foram selecionadas aleatoriamente 32 estações para o desenvolvimento do algoritmo e 17 para avaliação do desempenho de modo a representar todos os intervalos de concentração de Cl-a nos dois subconjuntos de dados. O desempenho do algoritmo obtido foi superior (r2 = 0,8424 e EMQ= 0,0418) ao dos algoritmos globais dos sensores SeaWIFS, OC2v4 (r2=0,77; EMQ=0,07), OC4v4 (r2=0,78;EMQ=0,07) e MODIS, OC3 (r2=0,79;EMQ=0,09) para os dados radiométricos, e também superior (r2=0,68; EMQ = 0,028) ao algoritmo global OC3 (r2= 0,62; EMQ= 0,036) para os dados de refletância do sensor MODIS, e apresentou melhor desempenho quanto à influência dos demais componentes bio-ópticos da água nos desvios das estimativas. Com base em dados de dois outros cruzeiros (setembro de 2005 e março de 2006), foi feita uma caracterização oceanográfica da plataforma adjacente à Baixada Santista, que mostrou que a região apresenta acentuada variabilidade sazonal e pode ser caracterizada como oligotrófica em termos de disponibilidade de nutrientes e biomassa fitoplanctônica. / A regional empirical algorithm for chlorophyll-a estimative in the continental shelf adjacent to Baixada Santista was developed based on in situ data on spectral radiometric and chlorophyll-a concentration obtained in 49 oceanographic stations during two oceanographic cruisers, in October 2005 and March 2006. Data from 32 stations were randomly selected for algorithm development and the other 17 for algorithm evaluation, representing all intervals of chlorophyll-a concentration in the two data subset. The performance of the regional algorithm was superior (r2 = 0,8424; RMS = 0,0418) to the global algorithms of the SeaWiFS, OC2v4 (r2=0,77; RMS=0,07), OC4v4 (r2=0,78;RMS=0,07) and MODIS, OC3 (r2=0,79; RMS=0,09) for the radiometric data, and also superior (r2=0,68; RMS = 0,028) to the global algorithm OC3 (r2= 0,62; RMS= 0,036) for reflectance data acquired by MODIS sensor. Also, the regional algorithm presented better performance, while estimative errors, related to the influence of other biooptical components of seawater. Based on the data of two other cruisers (September 2005 and March 2006), the oceanographic characterization of the continental shelf adjacent to Baixada Santista was made, revealing the region presents accentuate seasonal variability and can be characterized as oligotrophic in terms of nutrient availability and phytoplankton biomass.

Um algoritmo empírico regional para estimativa de clorofila-a na plataforma continental adjacente à Baixada Santista foi desenvolvido a partir de dados radiométricos e de concentração de clorofila-a, obtidos em 49 estações oceanográficas durante dois cruzeiros, em outubro de 2005 e março de 2006. Foram selecionadas aleatoriamente 32 estações para o desenvolvimento do algoritmo e 17 para avaliação do desempenho de modo a representar todos os intervalos de concentração de Cl-a nos dois subconjuntos de dados. O desempenho do algoritmo obtido foi superior (r2 = 0,8424 e EMQ= 0,0418) ao dos algoritmos globais dos sensores SeaWIFS, OC2v4 (r2=0,77; EMQ=0,07), OC4v4 (r2=0,78;EMQ=0,07) e MODIS, OC3 (r2=0,79;EMQ=0,09) para os dados radiométricos, e também superior (r2=0,68; EMQ = 0,028) ao algoritmo global OC3 (r2= 0,62; EMQ= 0,036) para os dados de refletância do sensor MODIS, e apresentou melhor desempenho quanto à influência dos demais componentes bio-ópticos da água nos desvios das estimativas. Com base em dados de dois outros cruzeiros (setembro de 2005 e março de 2006), foi feita uma caracterização oceanográfica da plataforma adjacente à Baixada Santista, que mostrou que a região apresenta acentuada variabilidade sazonal e pode ser caracterizada como oligotrófica em termos de disponibilidade de nutrientes e biomassa fitoplanctônica. / A regional empirical algorithm for chlorophyll-a estimative in the continental shelf adjacent to Baixada Santista was developed based on in situ data on spectral radiometric and chlorophyll-a concentration obtained in 49 oceanographic stations during two oceanographic cruisers, in October 2005 and March 2006. Data from 32 stations were randomly selected for algorithm development and the other 17 for algorithm evaluation, representing all intervals of chlorophyll-a concentration in the two data subset. The performance of the regional algorithm was superior (r2 = 0,8424; RMS = 0,0418) to the global algorithms of the SeaWiFS, OC2v4 (r2=0,77; RMS=0,07), OC4v4 (r2=0,78;RMS=0,07) and MODIS, OC3 (r2=0,79; RMS=0,09) for the radiometric data, and also superior (r2=0,68; RMS = 0,028) to the global algorithm OC3 (r2= 0,62; RMS= 0,036) for reflectance data acquired by MODIS sensor. Also, the regional algorithm presented better performance, while estimative errors, related to the influence of other biooptical components of seawater. Based on the data of two other cruisers (September 2005 and March 2006), the oceanographic characterization of the continental shelf adjacent to Baixada Santista was made, revealing the region presents accentuate seasonal variability and can be characterized as oligotrophic in terms of nutrient availability and phytoplankton biomass.

The zooplankton community of Marguerite Bay, western Antarctic Peninsula, was investigated in relation to variability in chlorophyll concentrations and sea ice dynamics, using a combination of satellite remote sensing techniques and plankton net data. SeaWiFS chlorophyll data were validated with concurrent in situ data measured by HPLC and fluoromentric methods, and results indicate that SeaWiFS chlorophyll is an accurate measure of in situ values when HPLC data are used as ground truth. Climatology data of SeaWiFS chlorophyll west of the Antarctic Peninsula showed that the Bellingshausen Sea and Marguerite Bay usually had higher and more persistent chlorophyll concentrations compared with northern regions. These predictable phytoplankton blooms could provide the Antarctic krill, Euphausia superba, with the food required for successful reproduction and larval survival. Unusually high krill reproduction in 2000/2001 was coincident with above-average chlorophyll concentrations throughout the study area and was followed by the largest juvenile recruitment since 1981. High larval densities at the shelf break along the Antarctic Peninsula may have resulted, in part, from krill spawning in the Bellingshausen Sea. Interannual differences in sea ice also probably contributed to the variability in larval krill abundances. Interannual differences were observed in the species composition of the zooplankton of Marguerite Bay during fall, and these were linked to variability in the environmental conditions. Thysanoessa macrura was the most abundant euphausiid in 2001, while Euphausia crystallorophias dominated in 2002, and E. superba had intermediate densities during both years. Copepods were more abundant in 2001 by a factor of 2.6. Copepods and T. macrura showed a rapid population response to unusually high chlorophyll concentrations in the Bellingshausen Sea and Marguerite Bay during spring-summer 2000/2001, whereas E. superba and E. crystallorophias had a longer term response and showed increased recruitment in fall 2002. There were no clear associations between the distribution of zooplankton and environmental conditions in fall; however there was a significant relationship between chlorophyll concentrations in the Bellingshausen Sea during the preceding spring and zooplankton patterns during fall.

Temporal and spatial variations in the Sea of Marmara based on monthly averages of chlorophyll a, which is the major indicator of phytoplankton biomass and primary production, recorded by SeaWiFS and MODIS-Aqua sensors at nearly 100 stations have been analyzed for the period of 1997-2007. Majority of phytoplankton blooms occur during the winter and spring seasons, followed by a smaller secondary bloom during the fall season. The majority of high magnitude blooms occur at the Eastern part of the Sea which may be attributed to an increase in the amount of discharge of water contaminated with nutrients originating on land where the industries are located. The correlations between monthly averages of sea surface temperature (SST) and corresponding chlorophyll a values are statistically significant (inverse) at 1% level, where r= -0.53 and the equation of the fitted model is: Chlorophyll a = 7.09199 &ndash / 0.215402* SST This correlation is expected because a relative decrease in SST is an indicative of upwelling and vertical mixing which are the primary processes for the formation of phytoplankton blooms. We have also found that monthly averages of chlorophyll a recorded by SeaWiFS and MODIS-Aqua are nearly identical and either data set can be used in place of the other.

SeaWiFS was collecting ocean color data since 1997. This means chlorophyll-a data for more than ten years. Since, SeaWiFS Chl-a data is validated for Black Sea this data set can be used for analysis. Nevertheless, the data is not gap free due to cloud effect. One of the main objectives of this work is to obtain a gap free, complete Chl-a data set for the Black Sea. For this purpose DINEOF method will be used.

Water quality in Tampa Bay was examined using concurrent in situ and satellite remote sensing observations. Chlorophyll and suspended sediment concentrations showed large short-term variability, primarily driven by tide and wind forcing. Superimposed on these high frequency variations were recurrent phytoplankton blooms stimulated by decreases in turbidity 1-2 days after wind-induced bottom sediment resuspension events; the blooms were particularly strong if neap tides occurred after the wind events. The in situ data show that observations once per month are inadequate to sample short-term variability and that therefore the current monthly water quality surveys may have uncertainties of -50 to 200% if they are used to represent the monthly mean concentrations of chlorophyll or suspended sediment. Such uncertainties make it difficult to identify trends and interannual variability based on the in situ monitoring program. Colored dissolved organic matter (CDOM) generally showed good relationship with salinity and primarily delivered by riverine inputs but showed conservative and non-conservative mixing behaviors for the dry and wet seasons, respectively. CDOM in Old Tampa Bay (OTB), however, showed properties that were different from those in other Bay segments, and the non-conservative CDOM mixing behavior may be simply due to a three-end-member mixing scenario in which Hillsborough Bay and Middle Tampa Bay also receive water from Old Tampa Bay. A turbidity algorithm was successfully developed for application of MODIS/Aqua 250 m imagery. The MODIS turbidity images showed distinct spatial and temporal patterns related to river runoff in the upper bay and wind-induced sediment resuspension events in the middle and lower portions of the Bay. Similarly, light attenuation from SeaWiFS estimated using a new semi-analytical algorithm confirmed that water clarity was related to river runoff and to wind-induced sediment resuspension events. Wind is shown repeatedly to be another important factor controlling water quality in the Bay. The study shows that remote sensing products have the potential to be an important tool to help resource managers assess conditions in a large estuary like Tampa Bay synoptically, frequently and repeatedly.

Fishing is a significant source of food, and constitutes an important source of income in Turkey. Due to the large extent required to analyse the distribution of fish stocks, information derived from satellites play an important role in fisheries applications. Chlorophyll concentration and sea surface temperature (SST) are the most significant parameters which define the fish habitat. The accuracy of these parameters in the Black Sea taken from two different satellites, namely Sea-viewing Wide Field-of-views Sensor (SeaWIFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) are evaluated. Results indicate that both satellites give good estimates of SST but the algorithms overestimate the chlorophyll concentration values. MODIS products are used in the subsequent analyses due to their high correlation with in-situ measurements relative to SeaWIFS products. The cause of the overestimation of chlorophyll concentration is further examined and a general description of environmental variability in Black Sea is done using MODIS products. Anchovy, the most important commercial fish in Turkey, has been selected as the target specie of the study. Level 3 weekly average MODIS chlorophyll and SST products are processed using remote sensing (RS) and geographic information systems (GIS) integration to estimate potential favorable zones for pelagic fish aggregations. Two different decision rules are employed to generate fish stock maps, simple additive weigthing (SAW) and fuzzy additive weigthing (FSAW). The resultant maps are used to visualize the general distribution of Anchovy in Turkish Seas from May 2000 to May 2001. The resultant thematic fish stock maps generated by FSAW analysis represents the uncertainity in the environment better than the ones generated by SAW analysis.

Data from five research cruises performed between 1997 and 2001 were processed in order to investigate the potential for improving remote sensing algorithms in the Estuary and Gulf of St. Lawrence. Measured in situ parameters included concentration-dependent indicators of the three critical, optically-active constituents, chlorophyll, Coloured Dissolved Organic Matter (CDOM) and Suspended Particulate Matter (SPM). The radiometric dataset used to investigate different types of algorithms consisted of multi-band above-surface remote sensing reflectance (R[subscript rs]) estimates. These estimates were computed from downwelling surface irradiance and upwelling sub-surface radiance measurements acquired using a SeaWiFS Profiler Multichannel Radiometer (SPMR). The chlorophyll data varied from approximately 0.1 to 17.3 mg.m[superscript -3] in the study region which extended from stations near the Saguenay River to the outer extremes of the Gulf of St. Lawrence. The CDOM and SPM concentration indicators were lower in the Gulf compared to the Estuary. Moderate correlation between in situ measurements was found between chlorophyll and SPM, as well as between CDOM and SPM. Chlorophyll and CDOM were virtually uncorrelated. The standard SeaWiFS Case-I chlorophyll retrieval algorithm, OC4v4, was applied to SPMR data acquired over a significant number of sampling stations (N=169). Algorithm shortcomings were noted when the OC4v4 algorithm was applied directly to the study region. Specific shortcomings, the overestimation of low, and underestimation of high chlorophyll concentrations were consistent with previous findings in coastal regions and particularly with previous findings in the NW Atlantic and in high latitude regions. In addition, the algorithmic output was found to be fairly strongly correlated with CDOM and SPM. A perturbation approach, based on the analysis of residuals between OC4v4 estimates and in situ data, showed that the retrieved chlorophyll biases (overestimates) were dependent on SPM and CDOM (especially at low in situ chlorophyll concentrations). An analysis of the spectral parameters (band ratios and spectral slopes) with respect to in situ constituent concentrations showed that both band ratios and band slopes have a greater dependency on CDOM and/or SPM than on chlorophyll. This observation was supported by radiative transfer calculations which showed that the variability of the blue-to-green band ratios due to changes in CDOM and SPM concentrations could be greater than the variability due to changes in chlorophyll concentration. These findings showed that there was no adequate, single band-ratio algorithm for the remote sensing of chlorophyll in our study region. Systematic testing of a large combination of spectral parameters within the context of specific algorithmic formulations resulted in seven prescribed algorithms which provided slight to moderate improvement in the correlation coefficients and root mean square errors relative to in situ chlorophyll and significant decorrelation relative to CDOM and SPM parameters. In general, algorithms based on multiple spectral parameters were more accurate predictors of in situ chlorophyll. In addition to new algorithms, a set of previous algorithms developed by Jacques (2000) for a subregion of the Estuary were validated in the present study. This validation demonstrated a rather remarkable robustness of correlations between in situ and spectral parameters across time and for different types of instruments and measuring conditions. A relatively smaller number of matching SeaWiFS pixels (N=39) and in situ measurements were used to evaluate the performance of the SPMR-derived algorithms. The accuracy of all algorithms deteriorated when applied to satellite data (one possible reason being the shortcomings of the atmospheric correction algorithm, as underscored by the existence of negative values in the reflectance data). Nonetheless, the improvement of the two selected algorithmic formulations relative to the OC4v4 algorithm showed a certain robustness in the face of environmental influences such as atmospheric effects and sensor response variations. Model simulations showed significant shortcomings of the new algorithms in specific turbidity conditions. The selected algorithms were shown to achieve chlorophyll retrievals which were as good as or better than OC4v4 retrievals. Even though the APD<35% accuracy target of the SeaWiFS project could not be reached, new algorithms succeeded to decrease the APD of the remote estimations from 226% to 65% for SPMR data, and from 502% to 95% for SeaWiFS data. In general, our findings showed that the selected algorithmic formulations had the potential for improving chlorophyll retrieval in the St. Lawrence Estuary and Gulf."--Résumé abrégé par UMI.