面向对象遥感分类方法在汶川地震震害提取中的应用
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摘要
震后城市建筑物震害的自动识别与分类,是遥感震害调查中的关键步骤,其精度直接影响损失评估的结果。而随着高分辨率遥感影像的发展,传统基于像元的分类技术已不能满足需求,引入面向对象的信息提取技术,充分挖掘影像对象的纹理、形状和相互关系等信息,能够有效的提高震害的分类精度。该文阐述了面向对象的遥感震害提取思路和方法,并应用汶川地震震后高分辨率航空遥感数据,针对建筑物震害进行面向对象的快速提取与自动分类。结果表明,与基于像元分类比较,面向对象的建筑物震害分类能够显著改善分类效果。
Automatic recognition and classification of building seismic disaster information is the key step of the seismic disaster evaluation.And its precision directly affects the result of loss evaluation.With the development of high-resolution remote sensing image,the traditional pixel-based classification is not able to meet the requirement.In order to fully excavate the texture,shape and relationship information of remote sensing data,we introduced an object-oriented method to improve the classification precision.Aiming at building seismic damage detection,object-oriented method was used in this paper to classify the post-earthquake aerial remote sensing images of the 2008 Wenchuan M8.0 earthquake.Compared to pixel-based classification,object-oriented method significantly improved the effect of damage detection.
Automatic recognition and classification of building seismic disaster information is the key step of the seismic disaster evaluation.And its precision directly affects the result of loss evaluation.With the development of high-resolution remote sensing image,the traditional pixel-based classification is not able to meet the requirement.In order to fully excavate the texture,shape and relationship information of remote sensing data,we introduced an object-oriented method to improve the classification precision.Aiming at building seismic damage detection,object-oriented method was used in this paper to classify the post-earthquake aerial remote sensing images of the 2008 Wenchuan M8.0 earthquake.Compared to pixel-based classification,object-oriented method significantly improved the effect of damage detection.
引文
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[2]柳稼航,杨建峰,魏成阶,等.震害信息遥感获取技术历史、现状和趋势[J].自然灾害学报,2004,13(5):46-52.
[3]蒲智,刘萍,杨辽,等.面向对象技术在城市绿地信息提取中的应用[J].福建林业科技,2006,33(1):40-44.
[4]丁晓英.eCognition在土地利用项目中的应用[J].测绘与空间地理信息,2005,28(6):116-117.
[5]孙晓霞,张继贤,刘正军.利用面向对象的分类方法从IKONOS全色影像中提取河流和道路[J].测绘科学,2006,31(1):62-63.
[6]王文宇,李博.基于eCogniton的高分辨率遥感图像的自动识别分类技术[J].北京建筑工程学院学报,2006,22(4):26-29.
[7]杜凤兰,田庆久,夏学齐,等.面向对象的地物分类法分析与评价[J].遥感技术与应用,2004,19(1):20-23.
[8]张振勇,王萍,朱鲁,等.eCognition技术在高分辨率遥感影像信息提取中的应用[J].国土资源信息化,2007,33(2):15-17.
[9]胡进刚,张晓东,沈欣,等.一种面向对象的高分辨率影像道路提取方法[J].遥感技术与应用,2006,21(3):184-188.
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