Genetic Algorithm for Oil Spill Automatic Detection from Envisat Satellite Data

Oil Spill Pollution Automatic Detection from MultiSAR Satellite Data Using Genetic Algorithm

“…This suggests that genetic algorithm is an excellent classifier to discriminate region of oil slicks from surrounding water features. This conforms the study of Marghany [30] and [31]. Figure 13.…”

“…Finally Marghany, [30] used Genetic algorithm for oil spill detection in ENVISAT ASAR data along Singapore Straits. He found that crossover process, and the fitness function generated accurate pattern of oil slick in SAR data.…”

“…This disaster has dominated by three months of oil flows in coastal waters of the Gulf of Mexico. Incidentally, the Deepwater Hoizon oil spill has serious effects on feeble maritime, wildlife habitats, Gulf's fishing, coastal ecologies and tourism industries [30,31]. Therefore, the resulting oil slicks are difficult to control, as their evolution be influenced by weather, currents, tides, and many chemical and physical factors [1][10] [31].…”

Genetic algorithm for oil spill automatic detection using synthetic aperture radar

“…Several SAR sensors are involved in the oil spill detection and survey. These data are from ERS-1/2, (Brekke and Solberg, 2005) ENVISAT (Marghany, 2013), ALOS, (Zhang et al, 2012), RADARSAT-1/2, (Zhang et al, 2012) and TerraSAR-X (Velotto et al, 2011) which have been globally, used to identify and monitor the oil-spill. Further, Airborne SAR sensors like Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR, by JPL, L-band) with a 22-km-wide ground swath at 22° to 65° incidence angles (Zhang et al, 2012) and E-SAR, (by DLR, multi-land) have also proven their excellent potential for monitoring coastal zone oil pollution.…”

“…These are considered as semi-automatic techniques. The main objective of this work is to examine GA (Marghany, 2013) for oil spill automatic detection in RADARSAT-2 SAR satellite data.…”