Characterization of local regularity in SAR Imagery by means of multiscale techniques: application to oil spill detection

In this paper, we develop algorithms for oil spill detection using radar remote sensing. The algorithms take into account both the mathematical and the physical modeling of the sea surface covered by oil slicks. We use the statistical characterization of the power reflectivity and its distribution under various oil thicknesses and electromagnetic wave frequencies. We first introduce a single frequency (SF) oil spill detector that uses single or multiple observations (SO or MO) of power reflection coefficients over several scanning iterations for the sea area. Then, using Monte Carlo simulations we address the correctness of this detector by choosing different frequencies. Results show the inability of this detector to effectively distinguish between oil slicks and oil-free slicks for the total range of possible thicknesses. Nevertheless, increasing the number of observations leads to an increase in the effectiveness of the detector. An upgrade of this detector is the dual-frequency (DF) detector using single and multiple observations where two electromagnetic frequencies are used at the same time. Performance analysis of this detector proves its ability to overcome the drawbacks of the first detector by providing accurate detection especially for multiple observations.

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Sea Oil Spill Detection Method Using SAR Imagery Combined with Object-Based Image Analysis and Fuzzy Logic

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1065-1069.3192 ◽

2014 ◽

Vol 1065-1069 ◽

pp. 3192-3200 ◽

Cited By ~ 2

Author(s):

Teng Fei Su ◽

Hong Yu Li ◽

Ting Xi Liu

Keyword(s):

Fuzzy Logic ◽

Oil Spill ◽

Oil Spills ◽

Promising Result ◽

Sar Images ◽

Oil Spill Detection ◽

Envisat Asar ◽

Object Based Image Analysis ◽

Object Based ◽

Sar Imagery

Synthetic aperture radar (SAR), a sensor with all weather and day and night working capacity, has been considered one of the most powerful tools for sea surface oil spill detection. However, lookalikes frequently appear in SAR images, limiting the operational use of SAR to detect oil spilled at sea. 20 scenes of Envisat ASAR images, which were acquired during the oil spill accident in the Gulf of Mexico in 2010, are utilized, with the objective to study how to better differentiate oil spills from lookalikes. 145 and 134 samples for oil spill and lookalike, respectively, are extracted, and their object-based geometric, physical and textural features are analyzed, in order to find the most effective features for oil spill classification. Based on the results of feature analysis, fuzzy logic (FL) is employed to construct a classifier for oil spill detection. One advantage of the proposed method is that it can produce the crisp probability of a dark segment being oil spill. The experiment shows that our method can derive promising result.

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Oil Spill Map for Indian Sea Region based on Bhuvan- Geographic Information System using Satellite Images

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-8-1085-2014 ◽

2014 ◽

Vol XL-8 ◽

pp. 1085-1090

Author(s):

L. J. Vijaya kumar ◽

J. K. Kishore ◽

P. Kesava Rao ◽

M. Annadurai ◽

C. B. S. Dutt ◽

...

Keyword(s):

Remote Sensing ◽

Oil Spill ◽

Oil Spills ◽

Geographic Information ◽

Gas Production ◽

Coast Guard ◽

Sar Images ◽

Distribution Maps ◽

Oil Spill Detection ◽

Sar Imagery

Oil spills in the ocean are a serious marine disaster that needs regular monitoring for environmental risk assessment and mitigation. Recent use of Polarimetric SAR imagery in near real time oil spill detection systems is associated with attempts towards automatic and unambiguous oil spill detection based on decomposition methods. Such systems integrate remote sensing technology, geo information, communication system, hardware and software systems to provide key information for analysis and decision making. <br><br> Geographic information systems (GIS) like BHUVAN can significantly contribute to oil spill management based on Synthetic Aperture Radar (SAR) images. India has long coast line from Gujarat to Bengal and hundreds of ports. The increase in shipping also increases the risk of oil spills in our maritime zone. The availability of RISAT-1 SAR images enhances the scope to monitor oil spills and develop GIS on Bhuvan which can be accessed by all the users, such as ships, coast guard, environmentalists etc., The GIS enables realization of oil spill maps based on integration of the geographical, remote sensing, oil & gas production/infrastructure data and slick signatures detected by SAR. SAR and GIS technologies can significantly improve the realization of oil spill footprint distribution maps. Preliminary assessment shows that the Bhuvan promises to be an ideal solution to understand spatial, temporal occurrence of oil spills in the marine atlas of India. The oil spill maps on Bhuvan based GIS facility will help the ONGC and Coast Guard organization.

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