A System for Automatic Identification of Oil Spill in ENVISAT ASAR Images

Author

Tian, Wei ; Shao, Yun ; Wang, Shiang

Author_Institution

State Key Lab. of Remote Sensing Sci., Jointly Sponsored by the Inst. of Remote Sensing Applic. of Chinese Acad. of Sci. & Beijing Normal Univ., Beijing

Volume

3

fYear

2008

fDate

7-11 July 2008

Abstract

An automatic oil spill identification system was introduced in this paper. It was designed to work independently to detect oil spills in ENVISAT ASAR level 1b images (of WS, IMP and APP mode). The absolute calibration, geometric correction without any GCPs, dark patches segmentation based on wind force levels, dark patches feature extraction, drifty trend prediction and identification confidence evaluation are the essential components of the system. The system works well for its accuracy of 85% in discriminating between oil spills and look-alikes in the case of 60 scenes of examined images.

Keywords

feature extraction; geophysical techniques; geophysics computing; image segmentation; marine pollution; oil pollution; remote sensing by radar; wind; APP mode; ENVISAT ASAR level 1b images; IMP mode; WS mode; absolute calibration; automatic oil spill identification system; dark patches feature extraction; dark patches segmentation; drifty trend prediction; geometric correction; identification confidence evaluation; wind force levels; Calibration; Equations; Feature extraction; Image segmentation; Petroleum; Radar scattering; Remote sensing; Sea surface; Surface discharges; Surface morphology; Envisat ASAR; Oil spill; drift; identification system; wind;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International

Conference_Location

Boston, MA

Print_ISBN

978-1-4244-2807-6

Electronic_ISBN

978-1-4244-2808-3

Type

conf

DOI

10.1109/IGARSS.2008.4779621

Filename

4779621