汶川地震前上空的地震云分析及自动检测研究

英文篇名：The Analysis and Automatic Detection of Earthquake Cloud before Wenchuan Earthquake
中文刊名：科学技术与工程
英文刊名：Science Technology and Engineering
作者：邹伟 ; 李元祥 ; 师春香 ; 邓雪原
英文作者：ZOU Wei1 ; LI Yuan-xiang1 ; SHI Chun-xiang2 ; DENG Xue-yuan3(School of Aeronautics & Astronautics ; Shanghai Jiaotong University1 ; Shanghai 200240 ; P.R.China ; National Satellite Meteorological Center ; CMA2 ; Beijing 100081 ; P.R.China ; School of Naval Architecture ; Ocean and Civil Engineering ; Shanghai Jiaotong University3 ; Shanghai 200240 ; P.R.China)
中文关键词：地震云 ; FY—2D ; MODIS ; 高斯马尔可夫场 ; 高斯混合模型
英文关键词：earthquake cloud FY—2D MODIS GMF GMM
出版日期：2011-08-08
机构：上海交通大学航空航天学院;国家卫星气象中心;上海交通大学船舶海洋与建筑工程学院;
年：2011
期：22
出版单位：科学技术与工程

摘要

地震对于人类的生产生活有着巨大影响,如何准确地预测地震意义重大。利用FY—2D卫星云图序列图像研究了汶川地震前震区上空的地震云,在此基础上采用更高分辨率的MOD IS数据进行地震云的检测研究,分别利用高斯马尔可夫场和高斯混合模型来实现云图的纹理分割和地震云异常检测。实验结果表明,此方法可有效检测出震区上空的地震云。
Earthquake has a huge impact on human life,how to accurately predict earthquakes is of great significance.The earthquake cloud over the area of Wenchuan is studed by FY—2D satellite cloud image sequences.On this basis,MODIS data with higher resolution is used for further verifying the earthquake cloud.Gaussian Markov Field(GMF) and Gaussian Mixture Model(GMM) are employed to achieve cloud texture segmentation and seismic anomaly detection respectively.Experimental results show that this method can effectively detect the earthquake cloud.

引文

1 Morozova L I.Dynamics of cloudy anomalies above fracture regionsduring natural and anthropogenic ally caused seismic activities.FizikaZemli,1997;9:94—96
    2 Park L.Unlocking the mystery of'Earthquake Clouds′-how they form&why Are they accurate in prediction.http://www.terraresearch.net/articles/earthquakeclouds_article1,2004
    3 Shou Z H.Earthquake clouds,a reliable precursor.Science and Uto-pya,1999;64:53—57
    4徐保华,徐秀登.地震云预测地震续探.科学技术与工程,2005;5(22):1705—1709
    5吕大炯,高建国,孙士鋐,等.地震云及其成因的探讨.自然杂志,1978;1(5):279—280
    6王斌,王丽丽.利用卫星云图预测地震.遥感信息,2006;5:52—55
    7 Pratt W.Digital image processing.NewYork:Wiley,1991:519—537
    8 Chellappa R,Chatterjee S.Classification of texture using GaussianMarkov random fields.IEEE Transactions on Acoustics,Speech,andSignal Processing,1985;33(4):959—963
    9孙即祥.现代目标识别.长沙:国防科技大学出版社,2002:31—36
    10 Stein D,Beaven S,Hoff L,et al.Anomaly detection from hyper-spectral imagery.IEEE Signal Processing Magazine,2002;19(1):58—69
    11 Steven M K.Fundamentals of statistical signal processing volumeⅡ:detection theory.Beijing:Electronic Industries Press,2006:501—505