Sea Oil Spill Detection Using Self-Similarity Parameter of Polarimetric Sar Data

Tong, Shengwu; Chen, Q.; Liu, X.

doi:10.5194/isprs-archives-xlii-3-1661-2018

Cited by 1 publication

(1 citation statement)

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“…The self-similarity parameter can be used to describe the randomness of the scattering mechanism of the target [32]. Compared to water and look-alikes, the randomness of scattering mechanisms in oil slicks is higher because of its complex scattering mechanism [33]. Hence, the self-similarity parameter was introduced to detect oil spills along with other seven polarimetric features.…”

Section: The Proposed Approachmentioning

confidence: 99%

Multi-Feature Based Ocean Oil Spill Detection for Polarimetric SAR Data Using Random Forest and the Self-Similarity Parameter

et al. 2019

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Synthetic aperture radar (SAR) is an important means to detect ocean oil spills which cause serious damage to the marine ecosystem. However, the look-alikes, which have a similar behavior to oil slicks in SAR images, will reduce the oil spill detection accuracy. Therefore, a novel oil spill detection method based on multiple features of polarimetric SAR data is proposed to improve the detection accuracy in this paper. In this method, the self-similarity parameter, which is sensitive to the randomness of the scattering target, is introduced to enhance the discrimination ability between oil slicks and look-alikes. The proposed method uses the Random Forest classification combing self-similarity parameter with seven well-known features to improve oil spill detection accuracy. Evaluations and comparisons were conducted with Radarsat-2 and UAVSAR polarimetric SAR datasets, which shows that: (1) the oil spill detection accuracy of the proposed method reaches 92.99% and 82.25% in two datasets, respectively, which is higher than three well-known methods. (2) Compared with other seven polarimetric features, self-similarity parameter has the better oil spill detection capability in the scene with lower wind speed close to 2–3 m/s, while, when the wind speed is close to 9–12 m/s, it is more suitable for oil spill detection in the downwind scene where the microwave incident direction is similar to the sea surface wind direction and performs well in the scene with incidence angle range from 29.7° to 43.5°.

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Section: The Proposed Approachmentioning

confidence: 99%