Issues and preliminary results in oil spill detection using optical remotely sensed images

Author

Cococcioni, Marco ; Corucci, Linda ; Lazzerini, Beatrice

Author_Institution

Dipt. di Ing. dell´´Inf.: Elettron., Inf., Telecomun., Univ. of Pisa, Pisa, Italy

fYear

2009

Firstpage

1

Lastpage

4

Abstract

An approach to oil spill detection is presented using optical satellite images. Features from SAR literature are studied. Different statistical and neural network-based classifiers are used in order to perform a supervised automatic classification and their performances are compared. The promising results achieved on the collected dataset encourage a further analysis of the potential of the optical oil spill detection approach.

Keywords

fuzzy systems; geophysics computing; microorganisms; neural nets; oceanographic techniques; oil pollution; optical images; pattern classification; remote sensing by radar; synthetic aperture radar; SAR literature; automatic classification; neural network; neuro-fuzzy system; oil spill detection; optical remote sensing image; pattern classification; synthetic-aperture radar; Adaptive optics; Backscatter; Neural networks; Optical detectors; Optical sensors; Petroleum; Radar detection; Satellites; Software architecture; Synthetic aperture radar; Neuro-Fuzzy Systems; Oil Spill Detection; Optical Satellite Images; Pattern Classification; Remote Sensing;

fLanguage

English

Publisher

ieee

Conference_Titel

OCEANS 2009 - EUROPE

Conference_Location

Bremen

Print_ISBN

978-1-4244-2522-8

Electronic_ISBN

978-1-4244-2523-5

Type

conf

DOI

10.1109/OCEANSE.2009.5278304

Filename

5278304