.png){kind=icon}
返回
Building-Based Damage Detection From Postquake Image Using Multiple-Feature Analysis
.png){kind=icon}
PRE
AI
DOI：10.1109/LGRS.2017.2651050.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Damaged building detection from high spatial resolution remote sensing image helps to rapid disaster losses assessment. However, the majority of traditional methods relies on only a single category feature of the damaged building. This letter presents a new strategy for detecting damaged buildings from postquake remote sensing image by multiple-feature analysis, in which the integrity of the building edge and the interior roof was both considered. The intactness of the building edge was assessed by proposing a new feature parameter, edge significance (ES), ES using significance test to quantify the difference between the gradient values on the edge and in the edge buffer. In addition, the gradient orientation inside the building was analyzed and local gradient orientation entropy (LOE) parameter was adopted to determine whether the interior roof was damaged. In general, damaged buildings have lower ES values because of broken edges and higher LOE values owing to debris, final decision was made on the basis of both feature parameters. A Quickbird image of Yushu, China, was used in the experiment and, among a total of 327 buildings, 266 were detected correctly. The overall accuracy was 84.10%, which is better than traditional methods.
Keyword:
Damaged building
earthquake
edge significance (ES)
local gradient orientation entropy (LOE)
remote sensing image
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
16.4
论文数:
1.0W
被引数:
5.1K
机构
引用论文
.png){kind=icon}
Bioinspired Tunable Helical Fiber-Shaped Strain Sensor with Sensing Controllability for the Rehabilitation of Hemiplegic Patients仿生可调谐螺旋纤维状应变传感器：具有传感可控性，用于偏瘫患者的康复
PREAI
分享收藏A comprehensive review of earthquake-induced building damage detection with remote sensing techniques遥感技术对地震引起的建筑物损坏检测的综合评述
PREAI
分享收藏
查看更多内容