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Neural Network for Oil Spill Detection using TerraSAR-X Data

Avezzano, Ruggero and Velotto, Domenico and Soccorsi, Matteo and Del Frate , Fabio and Lehner, Susanne (2011) Neural Network for Oil Spill Detection using TerraSAR-X Data. In: Proceedings of SPIE - SAR Image Analysis, Modeling, and Techniques XI, 8179 (817911), pp. 1-7. SPIE. SPIE Conference on Remote Sensing 2011, 19-22 September 2011, Prague, Czech Republic. ISBN 9780819488060. ISSN 0277-786X

Full text not available from this repository.

Official URL: http://dx.doi.org/10.1117/12.898645

Abstract

The increased amount of available Synthetic Aperture Radar (SAR) images involves a growing workload on the operators at analysis centers. In addition, even if the operators go through extensive training to learn manual oil spill detection, they can provide different and subjective responses. Hence, the upgrade and improvements of algorithms for automatic detection that can help in screening the images and prioritizing the alarms are of great benefit. In this paper we present the potentialities of TerraSAR-X (TS-X) data and Neural Network algorithms for oil spills detection. The radar on board satellite TS-X provides X-band images with a resolution of up to 1m. Such resolution can be very effective in the monitoring of coastal areas to prevent sea oil pollution. The network input is a vector containing the values of a set of features characterizing an oil spill candidate. The network output gives the probability for the candidate to be a real oil spill. Candidates with a probability less than 50% are classified as look-alikes. The overall classification performances have been evaluated on a data set of 50 TS-X images containing more than 150 examples of certified oil spills and well-known look-alikes (e.g. low wind areas, wind shadows, biogenic films). The preliminary classification results are satisfactory with an overall detection accuracy above 80

Document Type:Conference or Workshop Item (Poster)
Title:Neural Network for Oil Spill Detection using TerraSAR-X Data
Authors:
AuthorsInstitution or Email of Authors
Avezzano, RuggeroUniv. degli Studi di Roma Tor Vergata, Italy
Velotto, DomenicoUNSPECIFIED
Soccorsi, Matteomatteo.soccorsi@dlr.de
Del Frate , FabioUniv. degli Studi di Roma Tor Vergata, Italy
Lehner, SusanneUNSPECIFIED
Date:21 October 2011
Journal or Publication Title:Proceedings of SPIE - SAR Image Analysis, Modeling, and Techniques XI
Volume:8179
Page Range:pp. 1-7
Editors:
EditorsEmail
Notarnicola , ClaudiaEURAC research (Italy)
Paloscia, SimonettaIstituto di Fisica Applicata Nello Carrara (Italy)
Pierdicca , NazzarenoUniversità degli Studi di Roma La Sapienza (Italy)
Publisher:SPIE
Series Name:Proceedings of SPIE
ISSN:0277-786X
ISBN:9780819488060
Status:Published
Keywords:TerraSAR-X; Neural Network
Event Title:SPIE Conference on Remote Sensing 2011
Event Location:Prague, Czech Republic
Event Type:international Conference
Event Dates:19-22 September 2011
Organizer:SPIE
HGF - Research field:Aeronautics, Space and Transport (old)
HGF - Program:Space (old)
HGF - Program Themes:W EO - Erdbeobachtung
DLR - Research area:Space
DLR - Program:W EO - Erdbeobachtung
DLR - Research theme (Project):W - Vorhaben Entwicklung und Erprobung von Verfahren zur Gewässerfernerkundung (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Marine Remote Sensing
Deposited By: Bärbel Bolowski
Deposited On:19 Jan 2012 15:13
Last Modified:03 Apr 2013 15:50

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