Articles | Volume 17, issue 12
https://doi.org/10.5194/essd-17-6807-2025
https://doi.org/10.5194/essd-17-6807-2025
Data description paper
 | 
04 Dec 2025
Data description paper |  | 04 Dec 2025

Dataset of oil slicks, look-alikes and remarkable SAR signatures obtained from Sentinel-1 data in the Eastern Mediterranean Sea

Yi-Jie Yang, Suman Singha, Ron Goldman, and Florian Schütte

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Cited articles

Ahsbahs, T., Nygaard, N. G., Newcombe, A., and Badger, M.: Wind Farm Wakes from SAR and Doppler Radar, Remote Sensing, 12, https://doi.org/10.3390/rs12030462, 2020. a
Alpers, W. and Huang, W.: On the Discrimination of Radar Signatures of Atmospheric Gravity Waves and Oceanic Internal Waves on Synthetic Aperture Radar Images of the Sea Surface, IEEE Transactions on Geoscience and Remote Sensing, 49, 1114–1126, https://doi.org/10.1109/TGRS.2010.2072930, 2011. a, b, c, d
Alpers, W. and Zeng, K.: On Radar Signatures of Upwelling, Journal of Geodesy and Geoinformation Science, 4, 17, https://doi.org/10.11947/j.JGGS.2021.0102, 2021. a, b
Alpers, W., Huang, W., and Xilin, G.: Observations of atmospheric gravity waves over the Chinese seas by spaceborne synthetic aperture radar, Proc. Dragon (ESA SP-655), 2008. a
Alpers, W., Brandt, P., Lazar, A., Dagorne, D., Sow, B., Faye, S., Hansen, M. W., Rubino, A., Poulain, P.-M., and Brehmer, P.: A small-scale oceanic eddy off the coast of West Africa studied by multi-sensor satellite and surface drifter data, Remote Sensing of Environment, 129, 132–143, https://doi.org/10.1016/j.rse.2012.10.032, 2013. a
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This data descriptor presents a dataset containing oil slicks, look-alikes, and other remarkable ocean phenomena in synthetic aperture radar (SAR) data, which can be used for training oil spill detection methods. It explains the formation of various oceanic phenomena, supported by examples and supporting materials. These insights can help researchers from diverse backgrounds, such as remote sensing, oceanography, and machine learning, to better understand the sources of the signatures.
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