Investigating SAR algorithm for spaceborne interferometric oil spill detection

The environmental damages and recovery of terrestrial ecosystems from oil spills can last decades. Oil spills have been responsible for loss of aquamarine lives, organisms, trees, vegetation, birds and wildlife. Although there are several methods through which oil spills can be detected, it can be argued that remote sensing via the use of spaceborne platforms provides enormous benefits. This paper will provide more efficient means and methods that can assist in improving oil spill responses. The objective of this research is to develop a signal processing algorithm that can be used for detecting oil spills using spaceborne SAR interferometry (InSAR) data. To this end, a pendulum formation of multistatic smallSAR carrying platforms in a near equatorial orbit is described. The characteristic parameters such as the effects of incidence angles on radar backscatter, which support the detection of oil spills, will be the main drivers for determining the relative positions of the small satellites in formation. The orbit design and baseline distances between each spaceborne SAR platform will also be discussed. Furthermore, results from previous analysis on coverage assessment and revisit time shall be highlighted. Finally, an evaluation of automatic algorithm techniques for oil spill detection in SAR images will be conducted and results presented. The framework for the automatic algorithm considered consists of three major steps. The segmentation stage, where techniques that suggest the use of thresholding for dark spot segmentation within the captured InSAR image scene is conducted. The feature extraction stage involves the geometry and shape of the segmented region where elongation of the oil slick is considered an important feature and a function of the width and the length of the oil slick. For the classification stage, where the major objective is to distinguish oil spills from look-alikes, a Mahalanobis classifier will be used to estimate the probability of the extracted features being oil spills. The validation process of the algorithm will be conducted by using NASA’s UAVSAR data obtained over the Gulf of coast oil spill and RADARSAT-1 data.

[1]  Victoriano Moreno,et al.  An oil spill monitoring system based on SAR images , 1996 .

[2]  Terje Wahl,et al.  Oil spill detection using satellite based SAR: experience from a field experiment , 1993 .

[3]  Soo Chin Liew,et al.  Ocean oil pollution mapping with ERS synthetic aperture radar imagery , 1999, IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293).

[4]  Rune Solberg,et al.  Automatic detection of oil spills in ERS SAR images , 1999, IEEE Trans. Geosci. Remote. Sens..

[5]  M. Cherniakov,et al.  Bistatic radar : emerging technology , 2008 .

[6]  Gerhard Krieger,et al.  Analysis Of Satellite Configurations For Spaceborne SAR Interferometry , 2002 .

[7]  Tom Ziemke,et al.  Radar image segmentation using recurrent artificial neural networks , 1996, Pattern Recognit. Lett..

[9]  Howard A. Zebker,et al.  Decorrelation in interferometric radar echoes , 1992, IEEE Trans. Geosci. Remote. Sens..

[10]  Stan Matwin,et al.  Machine Learning for the Detection of Oil Spills in Satellite Radar Images , 1998, Machine Learning.

[11]  H. Hovland,et al.  Slick detection in SAR images , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[12]  M. Gade,et al.  On the detectability of marine oil pollution in European marginal waters by means of ERS SAR imagery , 2000, IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120).

[13]  Konstantinos N. Topouzelis,et al.  Oil Spill Detection by SAR Images: Dark Formation Detection, Feature Extraction and Classification Algorithms , 2008, Sensors.

[14]  Tao Zeng,et al.  Generalized approach to resolution analysis in BSAR , 2005, IEEE Transactions on Aerospace and Electronic Systems.

[15]  Kostas Topouzelis,et al.  Oil spill detection: SAR multiscale segmentation and object features evaluation , 2003, SPIE Remote Sensing.

[16]  Andrea Garzelli,et al.  Oil-spills detection in SAR images by fractal dimension estimation , 1999, IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293).

[17]  Fabio Del Frate,et al.  Neural networks for oil spill detection using ERS-SAR data , 2000, IEEE Trans. Geosci. Remote. Sens..

[18]  V. Wismann,et al.  Radar signatures of mineral oil spills measured by an airborne multi-frequency radar and the ERS-1 SAR , 1993, Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium.

[19]  Martin Gade,et al.  Remote Sensing of the European Seas , 2008 .

[20]  Tarchi Dario,et al.  Satellite Mapping of Oil Spills in the East Mediterranean Sea , 2006 .

[21]  G. Krieger,et al.  Comparison Of The Interferometric Performance For Spaceborne Parasitic SAR Configurations , 2002 .