This study aims to improve the process of characterizing oil on the sea surface using synthetic aperture radar (SAR) imagery, seeking to increase the accuracy of oil slick classification as natural or anthropogenic. A set of spatial attributes was obtained using semivariograms and phase-space pictures. This novel approach demonstrated potential to add value for monitoring seepage phenomena, which is of great scientific and environmental importance. The results achieved have potential for operational application as an aid in understanding active petroleum systems, reducing exploration risk in the decision-making process. Different targets display semivariograms with distinct geostatistical parameters, thus expressing contrasting models of spatial data correlation. The research results indicate that trajectories developed by the targets “sea”, “seepage slick”, and “oil spill” showed diagnostic behavior in their respective phase-space pictures.
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Gabrielle de Souza Brum
Fernando Pellon de Miranda
Tiago Mota
Remote Sensing
Universidade Federal do Rio de Janeiro
Pontifical Catholic University of Rio de Janeiro
Petrobras (Brazil)
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Brum et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69e1cecc5cdc762e9d857bee — DOI: https://doi.org/10.3390/rs18081189