Scheda di dettaglio – i prodotti della ricerca
| Dato | Valore |
|---|---|
| Title | A Specialized Support Vector Machine for Coastal Water Chlorophyll Retrieval from Water Leaving Reflectances |
| Abstract | Ocean colors observed by satellite are the measure of the water leaving reflectance of the investigated area, and vary according to the concentration of water's constituents. The relationship between satellite-derived ocean colors and chlorophyll a concentrations has been studied for several decades, and several model-based estimation algorithms have been proposed. Analytical models take account of all parameters relating water leaving reflectance with chlorophyll concentration. In empirical approaches remote sensed data is related to the chlorophyll concentration by interpolation techniques applied to a set of training samples. Several neural networks based algorithms have been proposed for the empirical approach. In a performance evaluation between several empirical approaches in inversion problems, shown that the use of the support vector machine (SVM) can improve the state of the art neural network solution. In this paper we propose a SVM specialized on Apulian coastal zones showing very encouraging results. |
| Source | Geoscience and Remote Sensing Symposium, Boston, MA, USA, 6-11 July 2008 |
| Keywords | ChlorophyllCoastal ZonesSVMprofilerWater Leaving Reflectances |
| Year | 2008 |
| Type | Contributo in atti di convegno |
| DOI | 10.1109/IGARSS.2008.4779871 |
| Authors | Raffaella Matarrese, A. Morea, K. Tijani, V. De Pasquale, M.T. Chiaradia, G. Pasquariello |
| Text | 347978 2008 10.1109/IGARSS.2008.4779871 Chlorophyll Coastal Zones SVM profiler Water Leaving Reflectances A Specialized Support Vector Machine for Coastal Water Chlorophyll Retrieval from Water Leaving Reflectances Raffaella Matarrese, A. Morea, K. Tijani, V. De Pasquale, M.T. Chiaradia, G. Pasquariello CNR IRSA, Politecnico di Bari, CNR ISSIA Ocean colors observed by satellite are the measure of the water leaving reflectance of the investigated area, and vary according to the concentration of water s constituents. The relationship between satellite derived ocean colors and chlorophyll a concentrations has been studied for several decades, and several model based estimation algorithms have been proposed. Analytical models take account of all parameters relating water leaving reflectance with chlorophyll concentration. In empirical approaches remote sensed data is related to the chlorophyll concentration by interpolation techniques applied to a set of training samples. Several neural networks based algorithms have been proposed for the empirical approach. In a performance evaluation between several empirical approaches in inversion problems, shown that the use of the support vector machine SVM can improve the state of the art neural network solution. In this paper we propose a SVM specialized on Apulian coastal zones showing very encouraging results. 978 1 4244 2807 6 Published version Geoscience and Remote Sensing Symposium Boston, MA, USA 6 11 July 2008 Internazionale Contributo Contributo in atti di convegno raffaella.matarrese MATARRESE RAFFAELLA guido.pasquariello PASQUARIELLO GUIDO |