A study on sea oil spill observation by means of polarimetric synthetic aperture radar (SAR) data is accomplished. It is based on the use of a polarimetric constant false alarm rate filter to detect dark patches over SAR images. Then, the target decomposition theorem is exploited to distinguish oil spills and look-alikes. Experiments are conducted on polarimetric SAR data acquired during the SIR-C/X-SAR mission on October 1994. The data were processed and calibrated at the Jet Propulsion Laboratory, National Aeronautics and Space Administration. Results show that the new polarimetric approach is able to assist classification
In this paper, a physical approach to support oil spills observation over synthetic aperture radar (SAR) images is presented. Electromagnetic model is based on an enhanced damping model that takes into account oil viscoelastic properties and wind speed. As a matter of fact, a multisensor approach is considered and a constant false alarm rate (CFAR) filter is used to minimize speckle effect. A set of experiments is presented and discussed. They show that oil spill processing is effective over single-look SAR images using mean input data
ENVISAT ASAR is successfully operating since March 2002 and resulting ASAR products are operationally distributed to the user community since December 2002.This paper provides an update of the ASAR performance, from the instrument status to the product quality assessment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.