Genetic Algorithm for Oil Spill Automatic Detection from Envisat Satellite Data

  • Maged Marghany
Conference paper

DOI: 10.1007/978-3-642-39643-4_42

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7972)
Cite this paper as:
Marghany M. (2013) Genetic Algorithm for Oil Spill Automatic Detection from Envisat Satellite Data. In: Murgante B. et al. (eds) Computational Science and Its Applications – ICCSA 2013. ICCSA 2013. Lecture Notes in Computer Science, vol 7972. Springer, Berlin, Heidelberg

Abstract

The merchant ship collided with a Malaysian oil tanker on May 25, 2010, and spilled 2,500 tons of crude oil into the Singapore Straits. The main objective of this work is to design automatic detection procedures for oil spill in synthetic aperture radar (SAR) satellite data. In doing so the genetic algorithm tool was designed to investigate the occurrence of oil spill in Malaysian coastal waters using ENVISAT ASAR satellite data. The study shows that crossover process, and the fitness function generated accurate pattern of oil slick in SAR data. This shown by 85% for oil spill, 5% look–alike and 10% for sea roughness using the receiver –operational characteristics (ROC) curve. It can therefore be concludedcrossover process, and the fitness function have the main role in genetic algorithm achievement for oil spill automatic detection in ENVISAT ASAR data.

Keywords

Oil Spill ENVISAT ASAR data Crossover Process Fitness Function Genetic algorithm 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Maged Marghany
    • 1
  1. 1.Institute of Geospatial Science and Technology (INSTeG)Universiti Teknologi MalaysiaSkudaiMalaysia

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