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Proceedings Paper

Automatic oil spill detection on quad polarimetric UAVSAR imagery
Author(s): Maryam Rahnemoonfar; Shanti Dhakal
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Paper Abstract

Oil spill on the water bodies has adverse effects on coastal and marine ecology. Oil spill contingency planning is of utmost importance in order to plan for mitigation and remediation of the oceanic oil spill. Remote sensing technologies are used for monitoring the oil spills on the ocean and coastal region. Airborne and satellite sensors such as optical, infrared, ultraviolet, radar and microwave sensors are available for remote surveillance of the ocean. Synthetic Aperture Radar (SAR) is used most extensively for oil-spill monitoring because of its capability to operate during day/night and cloud-cover condition. This study detects the possible oil spill regions on fully polarimetric Uninhabited Aerial Vehicle - Synthetic Aperture Radar (UAVSAR) images. The UAVSAR image is decomposed using Cloude-Pottier polarimetric decomposition technique to obtain entropy and alpha parameters. In addition, other polarimetric features such as co-polar correlation and degree of polarization are obtained for the UAVSAR images. These features are used to with fuzzy logic based classification to detect oil spill on the SAR images. The experimental results show the effectiveness of the proposed method.

Paper Details

Date Published: 12 May 2016
PDF: 7 pages
Proc. SPIE 9853, Polarization: Measurement, Analysis, and Remote Sensing XII, 985310 (12 May 2016); doi: 10.1117/12.2223966
Show Author Affiliations
Maryam Rahnemoonfar, Texas A&M Univ. Corpus Christi (United States)
Shanti Dhakal, Texas A&M Univ. Corpus Christi (United States)


Published in SPIE Proceedings Vol. 9853:
Polarization: Measurement, Analysis, and Remote Sensing XII
David B. Chenault; Dennis H. Goldstein, Editor(s)

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