Marghany, Maged Mahmoud and Hashim, Mazlan (2012) Automatic detection algorithms for oil spill from multisar data. In: Progress in Electromagnetics Research Symposium (PIERS 2012), 27-30 Mar 2012, Kuala Lumpur, Malaysia.
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Official URL: https://pdfs.semanticscholar.org/8cf4/e5fc2072c677...
Abstract
The main objective of this work is to develop comparative automatic detection procedures for oil spill pixels in multimode (Standard beam S2, Wide beam W1 and fine beam F1) RADARSAT-1 SAR satellite data that were acquired in the Malacca Straits using two algorithms namely, post supervised classification, and neural network (NN) for oil spill detection. The results show that NN is the best indicator for oil spill detection as it can discriminate oil spill from its surrounding such as look-alikes, sea surface and land. The receiver operator characteristic (ROC) is used to determine the accuracy of oil spill detection from RADARSAT-1 SAR data. In conclusion, that NN algorithm is an appropriate algorithm for oil spill automatic detecti
Item Type: | Conference or Workshop Item (Paper) |
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Uncontrolled Keywords: | Automatic detection procedures, oil spill, detection |
Subjects: | H Social Sciences > H Social Sciences (General) T Technology > TA Engineering (General). Civil engineering (General) |
Divisions: | Geoinformation and Real Estate |
ID Code: | 34009 |
Deposited By: | Liza Porijo |
Deposited On: | 22 Aug 2017 04:06 |
Last Modified: | 28 Sep 2017 06:26 |
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