Singha, Suman and Velotto, Domenico and Lehner, Susanne (2014) Near real time operational oil spill detection service using a classification tree. In: Proceedings of IEEE GOLD Remote Sensing Conference, June 2014, Berlin, Germany, pp. 1-3. IEEE GOLD Remote Sensing Conference, 4.-5. Juni 2014, Berlin, Germany.
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Official URL: http://ieee.uniparthenope.it/chapter/gold14.html
Abstract
Today the health of ocean is in danger due to over offshore oil exploration and increasing maritime traffic. Operational activities show regular occurrence of accidental and deliberate oil spill over major European shipping route and offshore platform locations. European oil spill detection service, ‘CleanSeaNet’ currently uses manual image interpretation technique in order to report oil spill to its member states. Anticipating regular and large amount of data from ESA’s Sentinal-1 mission (under Copernicus Service), a major focus of research in this area is the development of automated/semi-automated algorithms to distinguish oil spills from ‘look-alikes’ complementing the visual analysis carried out by current operational services. This paper describes the development of an semi-automated approach for oil spill detection from TerraSAR-X images using classification tree in Near Real Time (NRT) environment A total number of 8 feature parameters were extracted from 143 segmented dark-spot (oil spill and ‘look-alike’) representing different characteristic, which are then used to train the proposed Classification tree. An initial evaluation of this methodology has been carried out on a large dataset and reported
Item URL in elib: | https://elib.dlr.de/90652/ | ||||||||||||
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Document Type: | Conference or Workshop Item (Speech) | ||||||||||||
Title: | Near real time operational oil spill detection service using a classification tree | ||||||||||||
Authors: |
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Date: | November 2014 | ||||||||||||
Journal or Publication Title: | Proceedings of IEEE GOLD Remote Sensing Conference, June 2014, Berlin, Germany | ||||||||||||
Refereed publication: | No | ||||||||||||
Open Access: | No | ||||||||||||
Gold Open Access: | No | ||||||||||||
In SCOPUS: | No | ||||||||||||
In ISI Web of Science: | No | ||||||||||||
Page Range: | pp. 1-3 | ||||||||||||
Status: | Published | ||||||||||||
Keywords: | oil spill detection, near real time operational services, classification tree | ||||||||||||
Event Title: | IEEE GOLD Remote Sensing Conference | ||||||||||||
Event Location: | Berlin, Germany | ||||||||||||
Event Type: | international Conference | ||||||||||||
Event Dates: | 4.-5. Juni 2014 | ||||||||||||
Organizer: | Geoscience and Remote Sensing South Italy Chapter | ||||||||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||
HGF - Program: | Space | ||||||||||||
HGF - Program Themes: | Earth Observation | ||||||||||||
DLR - Research area: | Raumfahrt | ||||||||||||
DLR - Program: | R EO - Earth Observation | ||||||||||||
DLR - Research theme (Project): | R - Vorhaben Entwicklung und Erprobung von Verfahren zur Gewässerfernerkundung (old) | ||||||||||||
Location: | Bremen , Oberpfaffenhofen | ||||||||||||
Institutes and Institutions: | Remote Sensing Technology Institute > SAR Signal Processing | ||||||||||||
Deposited By: | Kaps, Ruth | ||||||||||||
Deposited On: | 26 Nov 2014 14:56 | ||||||||||||
Last Modified: | 28 Nov 2014 12:29 |
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