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      Obtención de perfiles de biomasa fitoplanctónica en bahía San Jorge (Antofagasta, Chile) a partir de imágenes en color Translated title: Phytoplankton biomass profiles in San Jorge Bay (Antofagasta, Chile) based on color imagery

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          Abstract

          Se realizaron mediciones de clorofila a mediante flurometría (CTD) con el fin de ajustar un modelo gaussiano y posteriormente obtener la distribución vertical de la biomasa fitoplanctónica en bahía San Jorge (norte de Chile) a partir de imágenes satelitales en color (MODIS-Aqua). Se realizó una calibración con datos in situ a partir de dos bases de datos. Los perfiles de clorofila a fueron suavizados con un promedio móvil, y se les ajustó un modelo gaussiano. Se obtuvieron los parámetros gaussianos promedio para ambas bases de datos. El modelo gaussiano promedio obtenido para una de las bases de datos fue válido para un intervalo de clorofila a de 1.17 a 51.8 mg m-3, y la máxima concentración subsuperficial se ubicó a los 19.20 y 0.25 m de profundidad, respectivamente. En la imagen en color del 20 de enero de 2011 analizada para el área de estudio, se observaron concentraciones de clorofila a con valor modal de 0.78 mg m-3, y el 95% de los datos fluctuó entre 0.5 y 20.0 mg m-3. El modelo gaussiano promedio ajustado fue válido para el 80.26% del área estudiada. Se amplió este estudio para el resto de enero (14 imágenes), y el modelo gaussiano fue válido para el 84.40% (±12.48%) del área estudiada. Al realizar un procedimiento similar sin aplicar un promedio móvil a los datos in situ, el modelo gaussiano ajustado promedio fue válido para el 93.72% (±8.89%) del área de estudio. Aún se requieren estudios sobre las propiedades ópticas del agua para mejorar la interpretación de las imágenes en color de este sistema costero.

          Translated abstract

          Fluorometric measurements were taken from a CTD at San Jorge Bay (northern Chile) to adjust a Gaussian model, in order to determine the vertical distribution of phytoplankton biomass using satellite-derived chlorophyll a data. Calibration was done using two in situ data sets. Each chlorophyll a profile was smoothed by a moving average and adjusted with a Gaussian model, obtaining the mean Gaussian parameters for both data sets. The mean Gaussian model obtained for one of the data sets was valid for a chlorophyll a range between 1.17 and 51.8 mg m-3, and the maximum concentration was located at 19.20 and 0.25 m depth, respectively. The 20 January 2011 color image was analyzed for the study area, and the modal concentration was 0.78 mg m-3, with 95% of the data varying between 0.5 and 20.0 mg m-3. The adjusted mean Gaussian model was valid for 80.26% of the study area. The analysis was expanded to the rest of January 2011 (14 images), and the model was valid for 84.40% (±12.48%) of the study area. The same procedure was followed but without applying the moving average to the in situ data, and the Gaussian model obtained in this case was valid for 93.72% (±8.89%) of the study area. Other studies of the optical properties of water are required for a better interpretation of the color images for this coastal system.

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          Most cited references40

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          Analysis of variations in ocean color1

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            The Deep Chlorophyll Maximum: Comparing Vertical Profiles of Chlorophylla

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              Oceanic primary production: estimation by remote sensing at local and regional scales.

              Satellites provide the only avenue by which marine primary production can be studied at ocean-basin scales. With maps of chlorophyll distribution derived from remotely sensed data on ocean color as input, deduction of a suitable algorithm for primary production is a problem in applied plant physiology. An algorithm is proposed that combines a spectral and angular model of submarine light with a model of the spectral response of algal photosynthesis. To apply the algorithm at large horizontal scale, a dynamic biogeography is needed for the physiological rate parameters and the biological structure of the water column. Fieldwork to obtain this type of data should be undertaken so that the use of satellite data in modern biological oceanography may be optimized.
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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Journal
                ciemar
                Ciencias marinas
                Cienc. mar
                Universidad Autónoma de Baja California, Instituto de Investigaciones Oceanológicas (Ensenada )
                0185-3880
                March 2014
                : 40
                : 1
                : 59-73
                Affiliations
                [1 ] Universidad de Antofagasta Chile
                [2 ] Universidad de Antofagasta Chile
                [3 ] Universidad de Antofagasta Chile
                Article
                S0185-38802014000100005
                10.7773/cm.v40i1.2345
                d8aafa1e-130b-43ff-baa2-c58bc82dcc7d

                http://creativecommons.org/licenses/by/4.0/

                History
                Categories
                Marine & Freshwater Biology

                Ecology
                chlorophyll α,Antofagasta Bay,MODIS-Aqua,remote sensing,clorofila α,bahía Antofagasta,detección remota

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