The availability of a nearly-continuous remotely-sensed chlorophyll 'a' maps (Chl a) from MODIS sensor, now longer than ten years, enables the assessment of multi-temporal trends for several locations around the world. In this paper the statistical method of the Support Vector Machine (SVM) has been applied to 5 years of MODIS data in order to generate Chl a maps. A Chl a multi-temporal analysis of Apulian region coastal zones in Southern Italy shows a positive trend in two test cases, confirming the increase of productivity in Southern Adriatic region found in the last years and demonstrating the simplicity and usefulness of this technique.
'Chlorophyll a' multi-temporal analysis in coastal waters with MODIS data
Matarrese Raffaella;
2011
Abstract
The availability of a nearly-continuous remotely-sensed chlorophyll 'a' maps (Chl a) from MODIS sensor, now longer than ten years, enables the assessment of multi-temporal trends for several locations around the world. In this paper the statistical method of the Support Vector Machine (SVM) has been applied to 5 years of MODIS data in order to generate Chl a maps. A Chl a multi-temporal analysis of Apulian region coastal zones in Southern Italy shows a positive trend in two test cases, confirming the increase of productivity in Southern Adriatic region found in the last years and demonstrating the simplicity and usefulness of this technique.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
