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...
Published in: | Remote Sensing |
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Main Authors: | , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
MDPI
2020
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Online Access: | https://hdl.handle.net/10037/17983 https://doi.org/10.3390/rs12071061 |
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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 |
collection | University of Tromsø: Munin Open Research Archive |
container_issue | 7 |
container_start_page | 1061 |
container_title | Remote Sensing |
container_volume | 12 |
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 |
genre | Arctic |
genre_facet | Arctic |
id | ftunivtroemsoe:oai:munin.uit.no:10037/17983 |
institution | Open Polar |
language | English |
op_collection_id | ftunivtroemsoe |
op_doi | https://doi.org/10.3390/rs12071061 |
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 https://hdl.handle.net/10037/17983 |
op_rights | openAccess Copyright 2020 The Author(s) |
publishDate | 2020 |
publisher | MDPI |
record_format | openpolar |
spelling | ftunivtroemsoe:oai:munin.uit.no:10037/17983 2025-04-13T14:12:06+00:00 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 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 2025-03-14T05:17:55Z 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 |
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 |
title | 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_short | 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 |
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 |
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 |
url | https://hdl.handle.net/10037/17983 https://doi.org/10.3390/rs12071061 |