NDLI: Automatic detection of oil spills in the Gulf of Mexico from RADARSAT-2 SAR satellite data

Content Provider	Springer Nature Link
Author	Marghany, Maged
Copyright Year	2015
Abstract	This work aimed to design optimization procedures for oil spill footprint automatic detection from synthetic aperture radar (SAR) satellite data. The main motivation of this work is to utilize a genetic algorithm (GA) without involving post-classification image processing tools for oil spill footprint boundary shape optimizations that involve local and global optimizations. The procedures are operated using sequences of RADARSAT-2 SAR ScanSAR Narrow single beam data acquired in the Gulf of Mexico. The study shows that the GA has high performance for oil spill boundary shape automatic optimization and detection. This provides evidence with standard error of 0.12 and non-significant differences with different acquisition dates. The ScanSAR Narrow mode data shows the extremely existing of 90 % of the oil spill footprint compared to the sea surface roughness and look-alikes. It can be said that Scan SAR Narrow mode can monitor oil spill disasters. In conclusion, the GA can be used as an automatic tool for oil spill without involving other post-image processing classification.
Starting Page	5935
Ending Page	5947
Page Count	13
File Format	PDF
ISSN	18666280
Journal	Environmental Earth Sciences
Volume Number	74
Issue Number	7
e-ISSN	18666299
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-06-21
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Oil spills Gulf of Mexico RADARSAT-2 SAR ScanSAR narrow beam Genetic algorithm Geology Hydrology/Water Resources Geochemistry Environmental Science and Engineering Terrestrial Pollution Biogeosciences
Content Type	Text
Resource Type	Article
Subject	Global and Planetary Change Earth-Surface Processes Soil Science Environmental Chemistry Pollution Geology Water Science and Technology

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