Remote Sensing | |
Knowledge-Based Detection and Assessment of Damaged Roads Using Post-Disaster High-Resolution Remote Sensing Image | |
Jianhua Wang3  Qiming Qin3  Jianghua Zhao2  Xin Ye3  Xiao Feng3  Xuebin Qin3  Xiucheng Yang3  Gonzalo Pajares Martinsanz1  | |
[1] Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China;;Scientific Data Center, Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China; E-Mails:;Institute of Remote Sensing and Geographic Information System, Peking University, Beijing 100871, China; E-Mails: | |
关键词: high-resolution remote sensing image; road centerline; knowledge model; damage detection; assessment indicator; | |
DOI : 10.3390/rs70404948 | |
来源: mdpi | |
【 摘 要 】
Road damage detection and assessment from high-resolution remote sensing image is critical for natural disaster investigation and disaster relief. In a disaster context, the pairing of pre-disaster and post-disaster road data for change detection and assessment is difficult to achieve due to the mismatch of different data sources, especially for rural areas where the pre-disaster data (
【 授权许可】
CC BY
© 2015 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
Files | Size | Format | View |
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RO202003190013527ZK.pdf | 2116KB | download |