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Quantifying the Impact of Linear Regression Model in Deriving Bio-Optical Relationships: The Implications on Ocean Carbon Estimations ArchiMer
Bellacicco, Marco; Vellucci, Vincenzo; Scardi, Michele; Barbieux, Marie; Marullo, Salvatore; D'Ortenzio, Fabrizio.
Linear regression is widely used in applied sciences and, in particular, in satellite optical oceanography, to relate dependent to independent variables. It is often adopted to establish empirical algorithms based on a finite set of measurements, which are later applied to observations on a larger scale from platforms such as autonomous profiling floats equipped with optical instruments (e.g., Biogeochemical Argo floats; BGC-Argo floats) and satellite ocean colour sensors (e.g., SeaWiFS, VIIRS, OLCI). However, different methods can be applied to a given pair of variables to determine the coefficients of the linear equation fitting the data, which are therefore not unique. In this work, we quantify the impact of the choice of regression method (i.e., either...
Tipo: Text Palavras-chave: Linear regression methods; Bio-optical properties; BGC-Argo; Satellite oceanography.
Ano: 2019 URL: https://archimer.ifremer.fr/doc/00585/69689/67568.pdf
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