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Remote Sensing surveillance constitutes an important component of oil spill disaster management system, but subject to
monitoring accuracy and ability, which suffered from resolution, environmental conditions, and look-alikes. So this
article aims to provide information of identification and distinguishing of look-alikes for optical sensors, and then
improve the monitoring precision. Although limited by monitoring conditions of the atmosphere and night, optical
satellite remote sensing can provide the intrinsic spectral information of the film and the background sea, then affords the
potentiality for detailed identification of the film thickness, oil type classification (crude/light oil), trends, and sea surface
roughness by multi-type data products. This paper focused on optical sensors and indicated that these false targets of sun
glint, bottom feature, cloud shadow, suspend bed sediment and surface bioorganic are the main factors for false alarm in
optical images. Based on the detailed description of the theory of oil spill detection in optical images, depending on the
preliminary summary of the feature of look-alikes in visible-infrared bands, a discriminate criteria and work-flow for
slicks identification are proposed. The results are helpful to improve the remote sensing monitoring ability and the
contingency planning.
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