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Urban Damage Assessment from Remotely Sensed Images
| Content Provider | Semantic Scholar |
|---|---|
| Author | Rejaie, Ali Shinozuka, Masanobu |
| Copyright Year | 2001 |
| Abstract | This study proposes a method to utilize remotely sensed preand post-disaster (bi-temporal) imagery data in order to detect the change specifically associated with structural and major regional damage caused by natural disasters such as a strong earthquake. The input is a pair of coregistered remotely sensed images of the same scene acquired at different times and the output is a binary image in which 'changed' pixels are separated from 'not-changed' ones. Correlation analysis generally fails to detect structural change, especially if images are acquired under different illumination conditions. In fact, automated detection in such a case becomes problematic since making distinction of change due to structural damage from that associated with the difference in the illumination condition is difficult. To overcome this problem, a method of principal component analysis (PCA) is employed. The approach produced promising results on the model images and currently under further study to be extended for near real-time damage assessment purposes. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://mceer.buffalo.edu/publications/resaccom/01-sp02/sra_ind/08.pdf |
| Alternate Webpage(s) | http://mceer.buffalo.edu/publications/sp_pubs/01-SP02/sra_ind/08.pdf |
| Alternate Webpage(s) | http://mceer.buffalo.edu/publications/resaccom/01-SP02/sra_ind/08.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
