Study on the Potential of Oil Spill Monitoring in a Port Environment Using Optical Reflectance
In this work, we studied the potential of the visible, near-infrared, and shortwave infrared wavelength regions for monitoring oil spill incidents using optical reflectance. First, a simple physical model was designed for accurate oil thickness and volume estimation using optical reflectance. The de...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-10-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/20/4950 |
| _version_ | 1827720001886355456 |
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| author | Bikram Koirala Nicholus Mboga Robrecht Moelans Els Knaeps Seppe Sels Frederik Winters Svetlana Samsonova Steve Vanlanduit Paul Scheunders |
| author_facet | Bikram Koirala Nicholus Mboga Robrecht Moelans Els Knaeps Seppe Sels Frederik Winters Svetlana Samsonova Steve Vanlanduit Paul Scheunders |
| author_sort | Bikram Koirala |
| collection | DOAJ |
| description | In this work, we studied the potential of the visible, near-infrared, and shortwave infrared wavelength regions for monitoring oil spill incidents using optical reflectance. First, a simple physical model was designed for accurate oil thickness and volume estimation using optical reflectance. The developed method was made invariant to changes in acquisition and illumination conditions. In the next step, an algorithm based on an artificial neural network was designed to detect spilled oil. The training samples that are required to optimize the parameters of the network were generated by utilizing the proposed physical model. To validate the method, experiments were conducted in laboratory and outdoor scenarios for detection and thickness/volume estimation on four different oil types. In particular, we developed hyperspectral datasets of oil samples with varying thickness between 500 µm and 5000 µm acquired using two different sensors, an Agrispec spectrometer and an Imec snapscan shortwave infrared hyperspectral camera, in strictly controlled experimental settings. To demonstrate the potential of the proposed method in outdoor environments using solely the visible wavelength region, we monitored the evolution of artificially spilled oil in an outdoor scene with an RGB camera mounted on a drone. |
| first_indexed | 2024-03-10T20:55:29Z |
| format | Article |
| id | doaj.art-3cc9a8201da94390a2559218fbbadca8 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T20:55:29Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-3cc9a8201da94390a2559218fbbadca82023-11-19T17:58:42ZengMDPI AGRemote Sensing2072-42922023-10-011520495010.3390/rs15204950Study on the Potential of Oil Spill Monitoring in a Port Environment Using Optical ReflectanceBikram Koirala0Nicholus Mboga1Robrecht Moelans2Els Knaeps3Seppe Sels4Frederik Winters5Svetlana Samsonova6Steve Vanlanduit7Paul Scheunders8Imec-Visionlab, University of Antwerp (CDE), Universiteitsplein 1, 2610 Antwerp, BelgiumInViLab Research Group, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, BelgiumVlaamse Instelling Voor Technologisch Onderzoek (VITO), Boeretang 200, 2400 Mol, BelgiumVlaamse Instelling Voor Technologisch Onderzoek (VITO), Boeretang 200, 2400 Mol, BelgiumInViLab Research Group, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, BelgiumRiskMatrix Group, Herkenrodesingel 4/1, 3500 Hasselt, BelgiumHaven van Antwerpen-Brugge/Port of Antwerp-Bruges, Zaha Hadidplein 1, 2030 Antwerpen, BelgiumInViLab Research Group, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, BelgiumImec-Visionlab, University of Antwerp (CDE), Universiteitsplein 1, 2610 Antwerp, BelgiumIn this work, we studied the potential of the visible, near-infrared, and shortwave infrared wavelength regions for monitoring oil spill incidents using optical reflectance. First, a simple physical model was designed for accurate oil thickness and volume estimation using optical reflectance. The developed method was made invariant to changes in acquisition and illumination conditions. In the next step, an algorithm based on an artificial neural network was designed to detect spilled oil. The training samples that are required to optimize the parameters of the network were generated by utilizing the proposed physical model. To validate the method, experiments were conducted in laboratory and outdoor scenarios for detection and thickness/volume estimation on four different oil types. In particular, we developed hyperspectral datasets of oil samples with varying thickness between 500 µm and 5000 µm acquired using two different sensors, an Agrispec spectrometer and an Imec snapscan shortwave infrared hyperspectral camera, in strictly controlled experimental settings. To demonstrate the potential of the proposed method in outdoor environments using solely the visible wavelength region, we monitored the evolution of artificially spilled oil in an outdoor scene with an RGB camera mounted on a drone.https://www.mdpi.com/2072-4292/15/20/4950hyperspectraloil spillmulti-sensor datasetRGB dataset |
| spellingShingle | Bikram Koirala Nicholus Mboga Robrecht Moelans Els Knaeps Seppe Sels Frederik Winters Svetlana Samsonova Steve Vanlanduit Paul Scheunders Study on the Potential of Oil Spill Monitoring in a Port Environment Using Optical Reflectance Remote Sensing hyperspectral oil spill multi-sensor dataset RGB dataset |
| title | Study on the Potential of Oil Spill Monitoring in a Port Environment Using Optical Reflectance |
| title_full | Study on the Potential of Oil Spill Monitoring in a Port Environment Using Optical Reflectance |
| title_fullStr | Study on the Potential of Oil Spill Monitoring in a Port Environment Using Optical Reflectance |
| title_full_unstemmed | Study on the Potential of Oil Spill Monitoring in a Port Environment Using Optical Reflectance |
| title_short | Study on the Potential of Oil Spill Monitoring in a Port Environment Using Optical Reflectance |
| title_sort | study on the potential of oil spill monitoring in a port environment using optical reflectance |
| topic | hyperspectral oil spill multi-sensor dataset RGB dataset |
| url | https://www.mdpi.com/2072-4292/15/20/4950 |
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