Mineral Oil Slicks Identification Using Dual Co-polarized Radarsat-2 and TerraSAR-X SAR Imagery

This study is devoted to a generalization of C-band Radarsat-2 and X-band TerraSAR-X synthetic aperture radar (SAR) data in the form of a diagram serving to easily identify mineral oil slicks (crude oil and emulsions) and separate them from the other oil slicks. The diagram is based on the multi-pol...

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Published in:Remote Sensing
Main Authors: Ivonin, Dmitry, Brekke, Camilla, Skrunes, Stine, Ivanov, Andrei, Kozhelupova, Nataliya
Format: Article in Journal/Newspaper
Language:English
Published: MDPI 2020
Subjects:
Online Access:https://hdl.handle.net/10037/17983
https://doi.org/10.3390/rs12071061
id ftunivtroemsoe:oai:munin.uit.no:10037/17983
record_format openpolar
spelling ftunivtroemsoe:oai:munin.uit.no:10037/17983 2023-05-15T14:27:34+02:00 Mineral Oil Slicks Identification Using Dual Co-polarized Radarsat-2 and TerraSAR-X SAR Imagery Ivonin, Dmitry Brekke, Camilla Skrunes, Stine Ivanov, Andrei Kozhelupova, Nataliya 2020-03-25 https://hdl.handle.net/10037/17983 https://doi.org/10.3390/rs12071061 eng eng MDPI Remote Sensing info:eu-repo/grantAgreement/RCN/NORRUSS/233896/Norway/Detection and Characterization of Anthropogenic Oil Pollution in the Barents Sea by Synthetic Aperture Radar// info:eu-repo/grantAgreement/RCN/PETROMAKS2/280616/Norway/Oil spill and newly formed sea ice detection, characterization, and mapping in the Barents Sea using remote sensing by SAR// info:eu-repo/grantAgreement/RCN/SFI/237906/Norway/Centre for Integrated Remote Sensing and Forecasting for Arctic Operations/CIRFA/ FRIDAID 1804573 doi:10.3390/rs12071061 2072-4292 https://hdl.handle.net/10037/17983 openAccess Copyright 2020 The Author(s) VDP::Technology: 500::Rock and petroleum disciplines: 510 VDP::Teknologi: 500::Berg‑ og petroleumsfag: 510 VDP::Mathematics and natural science: 400::Information and communication science: 420::Simulation visualization signal processing image processing: 429 VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Simulering visualisering signalbehandling bildeanalyse: 429 Journal article Tidsskriftartikkel Peer reviewed publishedVersion 2020 ftunivtroemsoe https://doi.org/10.3390/rs12071061 2021-06-25T17:57:22Z This study is devoted to a generalization of C-band Radarsat-2 and X-band TerraSAR-X synthetic aperture radar (SAR) data in the form of a diagram serving to easily identify mineral oil slicks (crude oil and emulsions) and separate them from the other oil slicks. The diagram is based on the multi-polarization parameter called Resonant to Non-resonant signal Damping (RND) introduced by Ivonin et al. in 2016, which is related to the ratio between damping within the slick of the short waves and wave breakings. SAR images acquired in the North Sea during oil-on-water exercises in 2011–2012 containing three types of oil spills (crude oil, emulsion, and plant oil) were used. The analysis was performed under moderate sea conditions (wind speeds of 2–6 m/s and sea wave heights of less than 2 m), the incidence angles of 27°–49°, and the signal-to-noise ratio (SNR) of −3 to 11 dB within slicks. On the diagram plane, created by the RND parameter and the Bragg wave number, the mineral oil samples form a well-outlined zone, called a mineral oil zone. For C-band data, the plant oil samples were clearly distinguished from the mineral oils in the diagram. Determination of the confidence level for the detection of mineral oils versus plant oil was proposed using the mineral oil zone boundaries. The mineral oil data with SNR within slicks better than 2 dB lay within this zone with a confidence level better than 65%. The plant oil data with the same SNR lay outside this zone with a confidence level of better than 80%. For mineral oil with SNR of −3 dB, the confidence level is 55%. Article in Journal/Newspaper Arctic University of Tromsø: Munin Open Research Archive Remote Sensing 12 7 1061
institution Open Polar
collection University of Tromsø: Munin Open Research Archive
op_collection_id ftunivtroemsoe
language English
topic VDP::Technology: 500::Rock and petroleum disciplines: 510
VDP::Teknologi: 500::Berg‑ og petroleumsfag: 510
VDP::Mathematics and natural science: 400::Information and communication science: 420::Simulation
visualization
signal processing
image processing: 429
VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Simulering
visualisering
signalbehandling
bildeanalyse: 429
spellingShingle VDP::Technology: 500::Rock and petroleum disciplines: 510
VDP::Teknologi: 500::Berg‑ og petroleumsfag: 510
VDP::Mathematics and natural science: 400::Information and communication science: 420::Simulation
visualization
signal processing
image processing: 429
VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Simulering
visualisering
signalbehandling
bildeanalyse: 429
Ivonin, Dmitry
Brekke, Camilla
Skrunes, Stine
Ivanov, Andrei
Kozhelupova, Nataliya
Mineral Oil Slicks Identification Using Dual Co-polarized Radarsat-2 and TerraSAR-X SAR Imagery
topic_facet VDP::Technology: 500::Rock and petroleum disciplines: 510
VDP::Teknologi: 500::Berg‑ og petroleumsfag: 510
VDP::Mathematics and natural science: 400::Information and communication science: 420::Simulation
visualization
signal processing
image processing: 429
VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Simulering
visualisering
signalbehandling
bildeanalyse: 429
description This study is devoted to a generalization of C-band Radarsat-2 and X-band TerraSAR-X synthetic aperture radar (SAR) data in the form of a diagram serving to easily identify mineral oil slicks (crude oil and emulsions) and separate them from the other oil slicks. The diagram is based on the multi-polarization parameter called Resonant to Non-resonant signal Damping (RND) introduced by Ivonin et al. in 2016, which is related to the ratio between damping within the slick of the short waves and wave breakings. SAR images acquired in the North Sea during oil-on-water exercises in 2011–2012 containing three types of oil spills (crude oil, emulsion, and plant oil) were used. The analysis was performed under moderate sea conditions (wind speeds of 2–6 m/s and sea wave heights of less than 2 m), the incidence angles of 27°–49°, and the signal-to-noise ratio (SNR) of −3 to 11 dB within slicks. On the diagram plane, created by the RND parameter and the Bragg wave number, the mineral oil samples form a well-outlined zone, called a mineral oil zone. For C-band data, the plant oil samples were clearly distinguished from the mineral oils in the diagram. Determination of the confidence level for the detection of mineral oils versus plant oil was proposed using the mineral oil zone boundaries. The mineral oil data with SNR within slicks better than 2 dB lay within this zone with a confidence level better than 65%. The plant oil data with the same SNR lay outside this zone with a confidence level of better than 80%. For mineral oil with SNR of −3 dB, the confidence level is 55%.
format Article in Journal/Newspaper
author Ivonin, Dmitry
Brekke, Camilla
Skrunes, Stine
Ivanov, Andrei
Kozhelupova, Nataliya
author_facet Ivonin, Dmitry
Brekke, Camilla
Skrunes, Stine
Ivanov, Andrei
Kozhelupova, Nataliya
author_sort Ivonin, Dmitry
title Mineral Oil Slicks Identification Using Dual Co-polarized Radarsat-2 and TerraSAR-X SAR Imagery
title_short Mineral Oil Slicks Identification Using Dual Co-polarized Radarsat-2 and TerraSAR-X SAR Imagery
title_full Mineral Oil Slicks Identification Using Dual Co-polarized Radarsat-2 and TerraSAR-X SAR Imagery
title_fullStr Mineral Oil Slicks Identification Using Dual Co-polarized Radarsat-2 and TerraSAR-X SAR Imagery
title_full_unstemmed Mineral Oil Slicks Identification Using Dual Co-polarized Radarsat-2 and TerraSAR-X SAR Imagery
title_sort mineral oil slicks identification using dual co-polarized radarsat-2 and terrasar-x sar imagery
publisher MDPI
publishDate 2020
url https://hdl.handle.net/10037/17983
https://doi.org/10.3390/rs12071061
genre Arctic
genre_facet Arctic
op_relation Remote Sensing
info:eu-repo/grantAgreement/RCN/NORRUSS/233896/Norway/Detection and Characterization of Anthropogenic Oil Pollution in the Barents Sea by Synthetic Aperture Radar//
info:eu-repo/grantAgreement/RCN/PETROMAKS2/280616/Norway/Oil spill and newly formed sea ice detection, characterization, and mapping in the Barents Sea using remote sensing by SAR//
info:eu-repo/grantAgreement/RCN/SFI/237906/Norway/Centre for Integrated Remote Sensing and Forecasting for Arctic Operations/CIRFA/
FRIDAID 1804573
doi:10.3390/rs12071061
2072-4292
https://hdl.handle.net/10037/17983
op_rights openAccess
Copyright 2020 The Author(s)
op_doi https://doi.org/10.3390/rs12071061
container_title Remote Sensing
container_volume 12
container_issue 7
container_start_page 1061
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