| 基于最优分割的高分辨率遥感影像震害建筑物识别技术 |
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| 引用本文： | 杜妍开,龚丽霞,李强,张景发.基于最优分割的高分辨率遥感影像震害建筑物识别技术[J].地震学报,2020,42(6):760-768. |
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| 作者姓名： | 杜妍开 龚丽霞 李强 张景发 |
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| 作者单位： | 中国北京 100085 应急管理部国家自然灾害防治研究院 |
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| 基金项目： | 中国地震局地壳应力研究所中央级公益性科研院所基本科研业务费专项（ZDJ2018-14）资助 |
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| 摘 要： | 为了提高建筑物震害信息提取的效率与准确度，针对震后高分辨率遥感影像，根据震害建筑物在遥感影像上的特征，以2010年海地MS7.0地震为例，通过尺度参数估计算法自动选择最优分割尺度对影像进行多尺度分割，并采用面向对象方法对海地高分辨率遥感影像进行建筑物震害信息提取，同时与基于像元的支持向量机、反向传播神经网络、基于分类回归算法的决策树分类方法进行比较。试验结果表明，面向对象的分类方法具有更好的目视效果和更高的分类精度，有利于地震后震害信息的准确提取和快速评估。
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| 关 键 词： | 面向对象 震害建筑物 高分辨率遥感影像 多尺度分割 |
| 收稿时间： | 2020-02-24 |
Earthquake damage building identification technology based on high resolution remote sensing image with optimal segmentation |
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| Institution: | National Institute of Natural Hazards，Ministry of Emergency Management of China，Beijing 100085，China |
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| Abstract: | In order to improve the efficiency and the accuracy of information extraction about earthquake damage building, based on high resolution remote sensing image after the earthquake, and according to the features of earthquake damage buildings in remote sensing images, we took a case study of MS7.0 Haiti earthquake in 2010, through the ESP algorithm automatically chose the optimal segmentation scale to multi-scale segmentation of images, used object-oriented method to Haiti high-resolution remote sensing image information extraction of earthquake damage buildings. At the same time, it is compared with Support Vector Machine based on pixel, BP neural network and Decision Tree classification method based on CART algorithm, the experimental results show that the object-oriented classification method has better visual effect and higher classification accuracy, which is beneficial to the accurate extraction and rapid evaluation of earthquake damage information after the earthquake. |
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