基于极化参数的SVM海上溢油识别

海洋学研究 ›› 2013, Vol. 31 ›› Issue (3): 71-75.

基于极化参数的SVM海上溢油识别

邹亚荣, 梁超, 曾韬

国家卫星海洋应用中心,北京 100081

收稿日期:2012-08-29 修回日期:2013-05-23 出版日期:2013-09-15 发布日期:2022-11-29
作者简介:邹亚荣(1967-),男,江西南昌市人,博士,主要从事海洋遥感应用研究。E-mail: zyr@mail.nsoas.gov.cn
基金资助:
国家海洋公益性行业科研专项经费项目资助(201205012);海洋执法监察等船舶飞机运行费项目资助(卫星遥感业务运行)

Oil spill identification using SVM based on polarization parameters

ZOU Ya-rong, LIANG Chao, ZENG Tao

National Satellite Ocean Application Service, Beijing 100081, China

Received:2012-08-29 Revised:2013-05-23 Online:2013-09-15 Published:2022-11-29

摘要/Abstract

摘要： 溢油对海洋环境造成的危害越来越大,及早发现对于减灾防灾具有重要意义。目前,运用极化SAR进行溢油探测已成为遥感监测的一个重要方面,本文基于SIR-C数据,开展极化SAR的溢油监测,提取极化参数熵H,散射角α和反熵A,运用SVM监督分类方法,进行溢油信息提取。结果表明,基于SVM的分类精度要强于基于H-α分类的分类结果。

关键词: 极化SAR, 溢油识别, SVM, 试验

Abstract: Due to the fact that oil spill has been increasing damage to the marine environment, to quickly detect the oil spill is certainly of significance for preventing and alleviating the disasters. Currently using polarized SAR in the detection of the oil spill is an important approach of remote sensing. In this paper, the SIR-C data were employed in the monitoring of oil spills, in which the polarized parameters entropy, scattering angle and anti-entropy were first extracted and then used to retrieve the oil spill information using the support vector machine (SVM) classifier. The assessment showed that SVM-based classification can achieve more accurate result than that of H-α decomposition based oil spill identification of SAR data.

Key words: polarization SAR, oil spill identification, SVM, test

中图分类号:

TN957.52
X55

邹亚荣, 梁超, 曾韬. 基于极化参数的SVM海上溢油识别[J]. 海洋学研究, 2013, 31(3): 71-75.

ZOU Ya-rong, LIANG Chao, ZENG Tao. Oil spill identification using SVM based on polarization parameters[J]. Journal of Marine Sciences, 2013, 31(3): 71-75.

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