Oil spill detection and characterization using fully-polarimetric X and C band SAR imagery: A near real time perspective
Singha S, Ressel R, Lehner S (2016)
Publication Type: Conference contribution
Publication year: 2016
Journal
Publisher: European Space Agency
Book Volume: SP-740
Conference Proceedings Title: European Space Agency, (Special Publication) ESA SP
Event location: Prague, CZE
ISBN: 9789292213053
Abstract
We explores the possibilities and advantages of quad polarimetric SAR data for the purpose of oil spill detection and discrimination of different types of slicks and lookalikes. An array of polarimetric features derived from the Pauli and lexicographic basis scattering matrices have been proposed. Those sets of features are then used to train and validate an Artificial Neural Network classifier. On a dataset of near-coincident TerraSAR-X (TS-X) and RADARSAT-2 (RS-2) acquisitions, we perform a feature analysis in terms of relevance and redundancy for oil slick characterization and ranked according to their ability to discriminate between oil spills and look-alikes. Polarimetric features such as Scattering diversity, Surface scattering fraction, Entropy and Span proved to be more discriminative than other polarimetric features.
Involved external institutions
Germany (DE)How to cite
APA:
Singha, S., Ressel, R., & Lehner, S. (2016). Oil spill detection and characterization using fully-polarimetric X and C band SAR imagery: A near real time perspective. In L. Ouwehand (Eds.), European Space Agency, (Special Publication) ESA SP. Prague, CZE: European Space Agency.
MLA:
Singha, Suman, Rudolf Ressel, and Susanne Lehner. "Oil spill detection and characterization using fully-polarimetric X and C band SAR imagery: A near real time perspective." Proceedings of the Living Planet Symposium 2016, Prague, CZE Ed. L. Ouwehand, European Space Agency, 2016.
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