Brekke, C., & Solberg, A. (2005). Oil spill detection by satellite remote sensing. Remote Sensing of Environment,
95, 1–13.
Article
Google Scholar
Choudhury, I., & Chakraborty, M. (2006). SAR signature investigation of rice crop using RADARSAT data. International Journal of Remote Sensing,
27, 519–534.
Article
Google Scholar
Davis, L. (1991). The handbook of genetic algorithms. New York: Van Nostran Reingold.
Google Scholar
Fiscella, B., Giancaspro, A., Nirchio, F., Pavese, P., & Trivero, P. (2000). Oil spill detection using marine SAR images. International Journal of Remote Sensing,
21, 3561–3566.
Article
Google Scholar
Frate, F. D., Petrocchi, A., Lichtenegger, J., & Calabresi, G. (2000). Neural networks for oil spill detection using ERS-SAR data. IEEE Transactions on Geoscience and Remote Sensing,
38, 2282–2287.
Article
Google Scholar
Garcia-Pineda, O., MacDonald, I., Hu, C., Svejkovsky, J., Hess, M., Dukhovskoy, D., & Morey, S. L. (2013a). Detection of floating oil anomalies from the Deepwater Horizon oil spill with synthetic aperture radar. Oceanography,
26(2), 124–137. doi:10.5670/oceanog.2013.38.
Article
Google Scholar
Garcia-Pineda, O., MacDonald, I. R., Li, X., Jackson, C. R., & Pichel, W. G. (2013b). Oil spill mapping and measurement in the Gulf of Mexico with textural classifier neural network algorithm (TCNNA). Selected Topics in Applied Earth Observations and Remote Sensing,
99, 1–9.
Google Scholar
Ivanov, A., He, M., & Fang, M. Q. (2002). Oil spill detection with the RADARSAT SAR in the waters of the Yellow and East Sea: A case study. In CD of 23rd Asian conference on remote sensing, Vol. 1, 13–17 November 2002, Nepal, Asian Remote Sensing Society, Japan, pp. 1–8.
Kahlouche, S., Achour, K., & Benkhelif, M. (2002). A new approach to image segmentation using genetic algorithm with mathematical morphology: In Proceedings of the 2002 WSEAS international conferences, Cadiz, Spain, 12–16 June 2002. www.wseas.us/e-library/conferences/spain2002/papers/443-164.pdf,1-5.
Marghany, M. (2001). RADARSAT automatic algorithms for detecting coastal oil spill pollution. International Journal of Applied Earth Observation and Geoinformation,
3(2), 191–196.
Article
Google Scholar
Marghany, M. (2013). Genetic algorithm for oil spill automatic detection from envisat satellite data. In B. Murgante, S. Misra, M. Carlini, C. M. Torre, H. Q. Nguyen, D. Taniar, B. O. Apduhan, & O. Gervasi (Eds.), Computational science and its applications—ICCSA 2013, Vol. 7972, pp. 587–598. Berlin, Heidelberg: Springer.
Marghany, M., & Hashim, M. (2011). Comparative algorithms for oil spill detection from multi mode RADARSAT-1 SAR satellite data. Lecture notes in computer science. In D. Taniar et al. (Eds.), Computational science and its applications—ICCSA 2011, Vol. 6783, pp. 318–329. Berlin, Heidelberg: Springer.
Matkan, A. A., Hajeb, M., & Azarakhsh, Z. (2013). Oil spill detection from SAR image using SVM based classification. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, SMPR,
1, W3.
Google Scholar
Maurizio, M., Ferdinando, N., Brown, C. E., Holt, B., Li, X., Pichel, W., & Shimada, M. (2012). Polarimetric synthetic aperture radar utilized to track oil spills. Eos, Transactions American Geophysical Union,
93(16), 161–162. doi:10.1029/2012EO160001.
Article
Google Scholar
McNutt, M. K., Camilli, R., Crone, T. J., Guthrie, G. D., Hsieh, P. A., Reyerson, T. B., et al. (2011). Review of flow rate estimates of the deepwater horizon oil spill. Proceedings of the National Academy of Sciences of the United States of America,
109, 20260–20267. doi:10.1073/pnas.1112139108.
Article
Google Scholar
MDA. (2009). RADARSAT-2 product description. Richmond, B.C., Canada. http://mdacorporation.com/geospatial/international/satellites/RADARSAT-2. Accessed 7 Mar 2014.
Michalewicz, Z. (1994). Genetic algorithms + data structures. Evolution programs. New York: Springer.
Book
Google Scholar
Minchew, B., Jones, C. E., & Holt, B. (2012). Polarimetric analysis of backscatter from the deepwater horizon oil spill using L-band synthetic aperture radar. IEEE Transactions on Geoscience and Remote Sensing,
50(10), 3812–3830. doi:10.1109/TGRS.2012.2185804.
Article
Google Scholar
RADARSAT-2. (2014). Satellite characteristics. Richmond, B.C., Canada. http://www.asccsa.gc.ca/eng/satellites/radarsat/radarsat-tableau.asp#RS2. Accessed 7 Mar 2014.
Shirvany, R., Chabert, M., & Tourneret, J.-Y. (2012). Ship and oil-spill detection using the degree of polarization in linear and hybrid/compact dual-pol SAR. Selected Topics in Applied Earth Observations and Remote Sensing,
5, 885–892.
Article
Google Scholar
Sivanandam, S. N., & Deepa, S. N. (2008). Introduction to genetic algorithms. Berlin: Springer.
Google Scholar
Skrunes, S., Brekke, C., & Eltoft, T. (2012). An experimental study on oil spill characterization by multi-polarization SAR. In Proceedings of European conference on synthetic aperture radar, Nuremberg, Germany, pp. 139–142.
Topouzelis, K. N. (2008). Oil spill detection by SAR images: Dark formation detection, feature extraction and classification algorithms. Sensors,
8(10), 6642–6659.
Article
Google Scholar
Topouzelis, K., Karathanassi, V., Pavlakis, P., & Rokos, D. (2007). Detection and discrimination between oil spills and look-alike phenomena through neural networks. ISPRS Journal Photogrametry Remote Sensing,
62, 264–270.
Article
Google Scholar
Topouzelis, K., Karathanassi, V., Pavlakis, P., & Rokos, D. (2009a). Potentiality of feed forward neural networks for classifying dark formations to oil spills and look-alikes. Geocarto International,
24, 179–191.
Article
Google Scholar
Topouzelis, K., Stathakis, D., & Karathanassi, V. (2009b). Investigation of genetic algorithms contribution to feature selection for oil spill detection. International Journal of Remote Sensing,
30(3), 611–625.
Article
Google Scholar
Velotto, D., Migliaccio, M., Nunziata, F., & Lehner, S. (2011). Dual-polarized terraSAR-X data for oil-spill observation. IEEE Transactions on Geoscience and Remote Sensing,
49, 4751–4762.
Article
Google Scholar
Zangari G. (2010). Risk of global climate change by bp oil spill. Frascati National Laboratories, Italy. www.associazionegeofisica.it/OilSpill.pdf. Accessed 7 March 2014.
Zhang, Y., Lin, H., Liu, Q., Hu, J., Li, X., & Yeung, K. (2012). Oil-spill monitoring in the coastal waters of Hong Kong and vicinity. Marine Geodesy,
35, 93–106.
Article
Google Scholar
Zhang, B., Perrie, W., Li, X., & Pichel, W. (2011). Mapping sea surface oil slicks using RADARSAT-2 quad-polarization SAR image. Geophysical Research Letter,
38, L10602.
Google Scholar