Application of synthetic aperture radar imagery for forward and backward tracking of oil slicks SCIE SCOPUS

Cited 2 time in WEB OF SCIENCE Cited 4 time in Scopus
Title
Application of synthetic aperture radar imagery for forward and backward tracking of oil slicks
Author(s)
Kim, Tae-Ho; Yang, Chan-Su; Ouchi, Kazuo
KIOST Author(s)
Yang, Chan Su(양찬수)
Alternative Author(s)
김태호; 양찬수
Publication Year
2019-08
Abstract
This paper presents a technique for tracking of oil slicks movement using synthetic aperture radar (SAR) and external force data with optimal coefficients. The detected oil from the SAR image is used as input data for tracking model, and wind and tidal current data are used as external forces to determine the displacement of oil slick. Forward and backward trackings were performed using a set of 4 SAR images observed at the time of the Hebei Spirit accident in 2007. The movement vectors are calculated using wind and tidal current with various coefficients. All tracking results show more than 56% accuracy. The new linear equations were calculated using coefficient values with the highest accuracy and velocity values of wind and tidal current. The modified equations were used to back-track from the satellite observation time to the accident occurrence time. The simulation results shows that most of the particles of the spread oil traced back around the point of the accident with little exceptions to some particles which shifted more than the oil spill. This is because the spill time of the particles are different from each other. Thus, the proposed method will contribute to the quick response activities and the estimation of location for the source of oil pollution.
ISSN
1017-0839
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/559
DOI
10.3319/TAO.2019.03.03.02
Bibliographic Citation
TERRESTRIAL ATMOSPHERIC AND OCEANIC SCIENCES, v.30, no.4, pp.509 - 519, 2019
Publisher
CHINESE GEOSCIENCE UNION
Keywords
Oil tracking; Marine weather data; SAR; Oil spill response technique; Backward tracking function
Type
Article
Language
English
Document Type
Article
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