地球信息科学学报 ›› 2012, Vol. 14 ›› Issue (2): 265-269.doi: 10.3724/SP.J.1047.2012.00265

• 遥感技术与应用 • 上一篇    下一篇

多元指标的海上溢油信息提取

邹亚荣*, 邹斌, 梁超, 崔松雪, 曾韬   

  1. 国家卫星海洋应用中心, 北京 100081
  • 收稿日期:2012-04-24 修回日期:2012-04-24 出版日期:2012-04-25 发布日期:2012-04-24
  • 基金资助:

    中国海监总队海洋执法飞机运行费(2012年);国家海洋局海洋溢油鉴别与损害评估技术重点实验室开发基金2009年(基于SAR散射的海上溢油监测算法研究)。

Multiple Index Information Extraction of Marine Oil Spills

ZOU Yarong, ZOU Bin, LIANG Chao, CUI Songxue, ZENG Tao   

  1. National Satellite Ocean Application Service, Beijing 100081, China
  • Received:2012-04-24 Revised:2012-04-24 Online:2012-04-25 Published:2012-04-24
  • Contact: 邹亚荣(1967-),男,江西南昌人,博士,研究员,从事海洋遥感与 GIS应用研究。E-mail: zyr@mail. nsoas.gov.cn E-mail:zyr@mail. nsoas.gov.cn

摘要: 海上溢油给海洋生态环境带来了巨大的影响,甚至需要几十年才能恢复。运用卫星遥感进行海上溢油监测已成为目前溢油监测的主要手段。本文对海上溢油遥感监测方法进行了分析,鉴此,提出了一种SAR数据的多元指标溢油信息提取方法。首先,对图像进行分割,然后,建立溢油形状参数、纹理特征指数、物理特性指数等主要指标,并以层次分析法得出每一类指标的权重。针对每一类指标,以经现场验证的溢油图像为基础,选择形状参数,如周长与面积比值、复杂度等,建立溢油形状判读等级;选择纹理特征参数,以灰度共生矩阵的相关性、熵、变化等来表达溢油的纹理特性,建立溢油纹理特征判断等级;选择溢油物理特征,如溢油与海水的标准差、均方根差、对比度等,建立溢油物理参数判断等级。在此基础上,建立海上溢油遥感信息提取指数,计算分割图斑的溢油遥感信息提取指数,以此判断溢油遥感信息提取的置信度,为溢油识别提供依据。

关键词: 多元指标, SAR, 溢油, 溢油遥感信息提取指数

Abstract: The oil spills bring great damage to the marine ecological environment even taking decades to repair. Using remote sensing technologies for marine oil spill detection has become a major direction. In this paper, through analyzing the marine oil spill remote sensing detection methods, a new one based on the multivariate index of oil spill information extraction with the SAR data is proposed. First, segmenting the images, and then establishing the shape parameters, the texture feature indexes, and the physical indexes of the spots, the indexes weights were given based on the hierarchical analysis method. For each category index, on the image processing with the on-site validation information, select shape parameters, e.g. the perimeter-to-area ratio, complexity, to establish oil spill shape interpretive level. Choose the texture characteristics parameters from the gray level co-occurrence matrix, e.g. relevance, entropy and change, to establish the oil spill texture feature judgment level. Choose the physical characteristics, e.g. the standard deviation, RMS and contrast, to establish the oil spill physical parameters judgment level. Finally, by calculating the remote sensing information extraction index of the segmentations image dark spots, we can evaluate the credibility of the oil spill remote sensing information extraction, even get a significant basis for the oil spill identification. From the paper, oil spill in the SAR image performance mechanism, the image characteristics and the shape aspects can comprehensively reflect oil spill remote sensing detection characteristics, and the three combination confidence in the remote sensing monitoring has certain practical value.

Key words: multiple index, SAR, oil spill, oil spill information extraction index