A FARIMA-based technique for oil slick and low-wind areas discrimination in sea SAR imagery

Author

Bertacca, Massimo ; Berizzi, Fabrizio ; Mese, Enzo Dalle

Author_Institution

Dept. of Inf. Eng., Univ. of Pisa, Italy

Volume

43

Issue

11

fYear

2005

Firstpage

2484

Lastpage

2493

Abstract

This paper introduces a new analysis technique, using the fractionally integrated autoregressive-moving average (FARIMA) model, to distinguish between low-wind and oil slick areas in high-resolution sea synthetic aperture radar (SAR) imagery. The method deals with the estimation of the fractional differencing and autoregressive-moving average parameters of the mean radial power spectral density of sea SAR images. The algorithm is applied and validated on dark areas corresponding to oil slicks, oil spills, and low-wind sea surface anomalies in European Remote Sensing 1 and 2 Precision Images of the Mediterranean Sea, North Sea, and Atlantic Ocean.

Keywords

oceanographic regions; oceanographic techniques; radar imaging; remote sensing by radar; synthetic aperture radar; Atlantic Ocean; European Remote Sensing; Mediterranean Sea; North Sea; autoregressive-moving average parameters; fractional differencing average parameter; fractionally integrated autoregressive-moving average; long-range dependence; low wind; oil slick; radial power spectral density; sea SAR imagery; sea surface anomaly; synthetic aperture radar; Amorphous materials; Brownian motion; Clutter; Fractals; Frequency; Image analysis; Petroleum; Remote sensing; Sea surface; Synthetic aperture radar; Fractionally integrated autoregressive-moving average (FARIMA) models; long-range dependence (LRD); oil slicks; synthetic aperture radar (SAR);

fLanguage

English

Journal_Title

Geoscience and Remote Sensing, IEEE Transactions on

Publisher

ieee

ISSN

0196-2892

Type

jour

DOI

10.1109/TGRS.2005.857622

Filename

1522609