Oil Spill Monitoring Based on SAR Remote Sensing Imagery

Abstract

Compared with traditional on-site oil spill monitoring, the use of remote sensing technology has the macroscopic characteristics, which could quickly and accurately find an oil spill area. Currently, the detection approach of monitoring the phenomenon of marine oil spill are usually divided into two types, which are optical and synthetic aperture radar SAR remote sensing imagery. Among all satellite sensors, SAR is still the most utilized for operational oil spill detection. Thus, adopt SAR imagery to achieve routinely monitoring. In the image analysis process, the discrimination of oil spills and look-alike phenomena e.g., low wind area, wind front area and natural slicks on SAR is a crucial task in marine oil spill. A support vector machine is employed to remote sensing image classification in this paper. Through the simulation of the Dalian oil spill event, the effectiveness of the proposed approach for SAR satellite image classification is verified.