Functional regression on remote sensing data in oceanography

摘要: The aim of this study is to propose the use a functional data analysis approach as an alternative classical statistical methods most commonly used in oceanography and water quality management. In particular we consider prediction total suspended solids (TSS) based on remote sensing (RS) data. For purpose several linear regression models non-functional are applied 10 years RS obtained from medium resolution imaging spectrometer sensor predict TSS concentration coastal zone Guadalquivir estuary. results approaches compared terms their mean square error values superiority established. A simulation has been designed order support these findings determine best model for parameter more general contexts.