Abstract
Remote Sensing (RS) data obtained from satellites are a type of spectral data which consist of reflectance values recorded at different wavelengths. This type of data can be considered as a functional data due to the continous structure of the spectrum. The aim of this study is to propose Functional Linear Regression Models (FLRMs) to analyze the turbidity in the coastal zone of Guadalquivir estuary from satellite data. With this aim different types of FLRMs for scalar response have been used to predict the amount of Total Suspended Solids (TSS) on RS data and their results have been compared.
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Acar-Denizli, N., Delicado, P., Başarır, G., Caballero, I. (2017). Functional linear regression models for scalar responses on remote sensing data: an application to Oceanography. In: Aneiros, G., G. Bongiorno, E., Cao, R., Vieu, P. (eds) Functional Statistics and Related Fields. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-55846-2_3
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DOI: https://doi.org/10.1007/978-3-319-55846-2_3
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