Earthquake-induced building damage detection with post-event sub-meter VHR terrasar-X staring spotlight imagery
文献类型：期刊论文
| 作者 | Gong, Lixia1; Wang, Chao1; Wu, Fan1; Zhang, Jingfa1; Zhang, Hong1; Li, Qiang1 |
| 刊名 | Remote Sensing
 |
| 出版日期 | 2016 |
| 卷号 | 8期号:11 |
| 关键词 | SURFACE-TEMPERATURE SATELLITE MODEL SIMULATIONS ASSIMILATION RETRIEVALS VEGETATION RESOLUTION RECORDS BASIN |
| 通讯作者 | Wu, Fan (wufan@radi.ac.cn) |
| 英文摘要 | Compared with optical sensors, Synthetic Aperture Radar (SAR) can provide important damage information due to its ability to map areas affected by earthquakes independently from weather conditions and solar illumination. In 2013, a new TerraSAR-X mode named staring spotlight (ST), whose azimuth resolution was improved to 0.24 m, was introduced for various applications. This data source made it possible to extract detailed information from individual buildings. In this paper, we present a new concept for individual building damage assessment using a post-event sub-meter very high resolution (VHR) SAR image and a building footprint map. With the building footprint map, the original footprints of buildings can be located in the SAR image. Based on the building imaging analysis of a building in the SAR image, the features in the building footprint can be extracted to identify standing and collapsed buildings. Three machine learning classifiers, including random forest (RF), support vector machine (SVM) and K-nearest neighbor (K-NN), are used in the experiments. The results show that the proposed method can obtain good overall accuracy, which is above 80% with the three classifiers. The efficiency of the proposed method is demonstrated based on samples of buildings using descending and ascending sub-meter VHR ST images, which were all acquired from the same area in old Beichuan County, China. © 2016 by the authors. |
| 学科主题 | Remote Sensing |
| 类目[WOS] | Remote Sensing |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:20164703032536 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39496]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1. Institute of Crustal Dynamics, China Earthquake Administration, Beijing 2.100085, China 3. School of Civil Engineering and Geosciences, Newcastle University, Newcastle Upon Tyne 4.NE1 7RU, United Kingdom 5. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 6.100094, China |
| 推荐引用方式 GB/T 7714 | Gong, Lixia,Wang, Chao,Wu, Fan,et al. Earthquake-induced building damage detection with post-event sub-meter VHR terrasar-X staring spotlight imagery[J]. Remote Sensing,2016,8(11). |
| APA | Gong, Lixia,Wang, Chao,Wu, Fan,Zhang, Jingfa,Zhang, Hong,&Li, Qiang.(2016).Earthquake-induced building damage detection with post-event sub-meter VHR terrasar-X staring spotlight imagery.Remote Sensing,8(11). |
| MLA | Gong, Lixia,et al."Earthquake-induced building damage detection with post-event sub-meter VHR terrasar-X staring spotlight imagery".Remote Sensing 8.11(2016). |
入库方式： OAI收割
来源：遥感与数字地球研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。