Share Email Print
cover

Proceedings Paper

Damaged road extracting with high-resolution aerial image of post-earthquake
Author(s): Zezhong Zheng; Chengjun Pu; Mingcang Zhu; Jun Xia; Xiang Zhang; Yalan Liu; Jiang Li
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

With the rapid development of earth observation technology, remote sensing images have played more important roles, because the high resolution images can provide the original data for object recognition, disaster investigation, and so on. When a disastrous earthquake breaks out, a large number of roads could be damaged instantly. There are a lot of approaches about road extraction, such as region growing, gray threshold, and k-means clustering algorithm. We could not obtain the undamaged roads with these approaches, if the trees or their shadows along the roads are difficult to be distinguished from the damaged road. In the paper, a method is presented to extract the damaged road with high resolution aerial image of post-earthquake. Our job is to extract the damaged road and the undamaged with the aerial image. We utilized the mathematical morphology approach and the k-means clustering algorithm to extract the road. Our method was composed of four ingredients. Firstly, the mathematical morphology filter operators were employed to remove the interferences from the trees or their shadows. Secondly, the k-means algorithm was employed to derive the damaged segments. Thirdly, the mathematical morphology approach was used to extract the undamaged road; Finally, we could derive the damaged segments by overlaying the road networks of pre-earthquake. Our results showed that the earthquake, broken in Yaan, was disastrous for the road, Therefore, we could take more measures to keep it clear.

Paper Details

Date Published: 9 December 2015
PDF: 6 pages
Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 980807 (9 December 2015); doi: 10.1117/12.2207415
Show Author Affiliations
Zezhong Zheng, Univ. of Electronic Science and Technology of China (China) and Guilin Univ. of Technology (China)
Wuhan Univ. (China) and Chengdu Univ. of Technology (China)
State Key Lab. of Remote Sensing Science (China)
Chengjun Pu, Univ. of Electronic Science and Technology of China (China) and Guilin Univ. of Technology (China)
Wuhan Univ. (China) and Chengdu Univ. of Technology (China)
State Key Lab. of Remote Sensing Science (China)
Mingcang Zhu, Land and Resources Department of Sichuan Province (China)
Jun Xia, Wuhan Univ. (China)
Xiang Zhang, Wuhan Univ. (China)
Yalan Liu, Institute of Remote Sensing and Digital Earth (China)
Jiang Li, Old Dominion Univ. (United States)


Published in SPIE Proceedings Vol. 9808:
International Conference on Intelligent Earth Observing and Applications 2015
Guoqing Zhou; Chuanli Kang, Editor(s)

© SPIE. Terms of Use
Back to Top