【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。更多还原

【Abstract】 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.更多还原