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Proceedings Paper

Marine oil pollution detection with MODIS data
Author(s): Lina Xu; Ruiqing Niu; Kang Xiao; Shenghui Fang; Yanfang Dong
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Paper Abstract

Marine oil pollution is one of the most serious pollutants on the damage to the contemporary marine environment, with the characteristics of a wide range of proliferation, which is difficult to control and eliminate. As a result, marine oil pollution has caused huge economic losses. The remote sensing sensors can detect and record the spectral information of sea film and background seawater. Here we chose to use 250-resolution MODIS data in the area of Dalian Xingang, China where ill spill case was happened on April.4th, 2005. Based on the image pre-processing and enhanced image processing, the spectral features of different bands were analyzed. More obvious characteristics of the spectral range of film was obtained. The oil-water contrast was calculated to evaluate the feature of oil at different spectral band. The result indicates that IR band has the maximum value of reflective. So band ratio was used between 400nm and 800nm and the original radiance images were used between 800nm and 2130nm. In order to get the most obvious images of entropy windows of different sizes were tested in order to decide the optimum window. At last, a FCM fuzzy clustering method and image texture analysis was combined for the MODIS images of the oil spill area segmentation. At last, the oil spill zone was estimated, the results were satisfied.

Paper Details

Date Published: 26 October 2013
PDF: 7 pages
Proc. SPIE 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 892106 (26 October 2013); doi: 10.1117/12.2030393
Show Author Affiliations
Lina Xu, China Univ. of Geosciences (China)
Wuhan Univ. (China)
Ruiqing Niu, China Univ. of Geosciences (China)
Kang Xiao, China Univ. of Geosciences (China)
Shenghui Fang, Wuhan Univ. (China)
Yanfang Dong, China Earthquake Administration (China)

Published in SPIE Proceedings Vol. 8921:
MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Jinwen Tian; Jie Ma, Editor(s)

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