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Review of oil spill remote sensing
Abstract
Remote-sensing for oil spills is reviewed. The use of visible techniques is ubiquitous, however it gives only the same results as visual monitoring. Oil has no particular spectral features that would allow for identification among the many possible background interferences. Cameras are only useful to provide documentation. In daytime oil absorbs light and remits this as thermal energy at temperatures 3-8K above ambient, this is detectable by infrared (IR) cameras. Laser fluorosensors are useful instruments because of their unique capability to identify oil on backgrounds that include water, soil, weeds, ice and snow. They are the only sensor that can positively discriminate oil on most backgrounds. Radar detects oil on water by the fact that oil will dampen water-surface capillary waves under low to moderate wave/wind conditions. Radar offers the only potential for large area searches, day/night and foul weather remote sensing.
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Cited by
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Hassanalian, M., & Abdelkefi, A. (2017) · Progress in Aerospace Sciences · doi:10.1016/j.paerosci.2017.04.003 · Cited by 1,454
The physical oceanography of the transport of floating marine debris
van Sebille, E., Aliani, S., Law, K. L., Maximenko, N., Alsina, J. M., Bagaev, A., Bergmann, M., Chapron, B., Chubarenko, I., Cózar, A., et al. (2020) · Environmental Research Letters · doi:10.1088/1748-9326/ab6d7d · Cited by 982
Leifer, I., Lehr, W. J., Simecek-Beatty, D., Bradley, E., Clark, R., Dennison, P., Hu, Y., Matheson, S., Jones, C. E., Holt, B., et al. (2012) · Remote Sensing of Environment · doi:10.1016/j.rse.2012.03.024 · Cited by 537
Big data meet green challenges: big data toward green applications
Wu, J., Guo, S., Li, J., & Zeng, D. (2016) · IEEE Systems Journal · doi:10.1109/jsyst.2016.2550530 · Cited by 389
Oil spills from global tankers: Status review and future governance
Chen, J., Zhang, W., Wan, Z., Li, S., Huang, T., & Fei, Y. (2019) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.04.020 · Cited by 391
Metadata
- Authors
- Fingas, M., & Brown, C.
- Venue
- Marine Pollution Bulletin
- Publisher
- Elsevier BV
- Published
- 2014-06
- Volume
- 83
- Issue
- 1
- Pages
- 9-23
- ISSN
- 0025-326X (ISSN-L)
- OpenAlex
- W2005902297
- Cited by
- 723
- References
- 0
- FWCI
- 36.25
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
