Title: Oil Spill Detection based on SAR and Metocean/Contextual Data Fusion
Authors: VESPE MICHELEPOSADA SANCHEZ MONICAFERRARO DI SILVI E CASTIGLIONE GuidoBULGARELLI BarbaraVAN WIMERSMA GREIDANUS HermanDJAVIDNIA Samuel
Citation: 33rd International Symposium on Remote Sensing of Environment, Sustaining the Millennium Development Goals - ISBN 978-0-932913-13-5 vol. I, II p. 862 - 865
Publisher: International Center for Remote Sensing of Environment (ICRSE)
Publication Year: 2009
JRC N°: JRC51304
URI: http://publications.jrc.ec.europa.eu/repository/handle/JRC51304
Type: Contributions to Conferences
Abstract: In this paper, an associative mapping data fusion approach to operational oil spill detection is investigated focusing on the combination of Synthetic Aperture Radar (SAR) imagery derived data, and ancillary information such as metocean and contextual data. The ancillary data related to the investigated area are processed together with the features of the detected dark objects extracted from the SAR image using Artificial Neural Networks, ultimately leading to the estimation of a reliability index of the oil spill detection. The detection reliability measure can be thought of as the likelihood of the object being an oil spill given the SAR, context and metocean available information.
JRC Institute:Institute for the Protection and Security of the Citizen

Files in This Item:
There are no files associated with this item.


Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.