基于SAR影像的海洋溢油监测方法适用性分析

Analysis on Adaptability of Monitoring Methods for Oil Spill by Using SAR Imagery

随着微波遥感技术的迅猛发展,利用SAR影像提取海洋溢油区域已成为监测海洋溢油的重要手段之一.首先介绍了利用SAR影像监测海洋溢油的基本原理并对主要监测方法进行适用性分析.在此基础上,利用SAR影像对珠江口担杆岛附近海面进行了海洋溢油的提取实验,并从提取精度与算法的消耗时间两个方面对各种监测方法对比分析.实验结果表明:人工神经网络法和最大类间方差法的提取结果较为接近,适用于大范围溢油监测.而马尔柯夫链法算法消耗时间长,但精度较高,更适用于实时监测溢油扩散这样的随机过程.

With the rapid development of microwave remote sensing, SAR technology has provided an effective way for monitoring oil spill. In this paper, we introduced the basic principle of monitoring oil spill by using SAR images. On the basis of that, we systematically analyzed the applicability of various methods for monitoring oil spill by using SAR images. The conclusion shows that the artificial neural network and the threshold method have the advantages of timeliness and efficiency in oil spill monitoring, while Markov Chain method has great development potential due to its capability in reducing the effect of internal ocean wave.