Multisensor Approach to Operational Oil Pollution Monitoring in Coastal Zones

Olga, L.; Marina, M.; Tatiana, B.; Andrey, K.; Vladimir, Krasnoselskikh

doi:10.1109/igarss.2008.4779619

Cited by 6 publications

(1 citation statement)

References 2 publications

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“…OLI/Landsat 8 optical data are available since 2013; OLI data using VIS/NIR channels with high spatial resolution (30 m) and thermal channels (100 m) have been largely employed in oil spill detection task and its efficiency has been sufficiently investigated. Oil spill were detected in coastal bay using OLI VIS/NIR channels by [19][20] . Oil film differs from sea water in thermal characteristics and absorption of sun rays energy.…”

Section: Introductionmentioning

confidence: 99%

Oil Spill Detection Using Otical Sensors: A Multi-Temporal Approach

Luciani

Laneve

2023

som

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Oil pollution is one of the most destructive consequences due to human activities in the marine environment. Oil wastes come from many sources and take decades to be disposed of. Satellite based remote sensing systems can be implemented into a surveillance and monitoring network. In this study, a multi-temporal approach to the oil spill detection problem is investigated. Change Detection (CD) analysis was applied to MODIS/Terra and Aqua and OLI/Landsat 8 images of several reported oil spill events, characterized by different geographic location, sea conditions, source and extension of the spill. Toward the development of an automatic detection algorithm, a Change Vector Analysis (CVA) technique was implemented to carry out the comparison between the current image of the area of interest and a dataset of reference image, statistically analyzed to reduce the sea spectral variability between different dates. The proposed approach highlights the optical sensors’ capabilities in detecting oil spills at sea. The effectiveness of different sensors’ resolution towards the detection of spills of different size, and the relevance of the sensors’ revisiting time to track and monitor the evolution of the event is also investigated.

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Section: Introductionmentioning

confidence: 99%