Change search
ReferencesLink to record
Permanent link

Direct link
Context-based mapping of damaged buildings from high-resolution optical satellite images
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics (closed 20110301).
2010 (English)In: International Journal of Remote Sensing, ISSN 0143-1161, E-ISSN 1366-5901, Vol. 31, no 13, 3411-3425 p.Article in journal (Refereed) Published
Abstract [en]

In the early stages of post-disaster response, a quick and reliable damage assessment map is essential.As time is a critical factor, automated damage mapping from remotely sensed images is the expected solution to drastically reduce data acquisition and computation time. Recently, high-resolution satellite images, such as QuickBird data, have been in high demand by damage assessment analysts and disaster management practitioners. However, the existing automated mapping approaches hardly accommodate such high-resolution data. This research aims at developing a new context-based automated approach for earthquake damage mapping from high-resolution satellite images. Relevant contextual information (including structure, shape, size, edge texture, spatial relations) describing the damage situation is formulated and up-scaled on a morphological scale-space. Speed optimization is achieved by parallel processing implementation. The developed approach was tested with two QuickBird images acquired on 26 June 2005 and 3 June 2008 over YingXiu town, Sichuan, China, which suffered the devastating 12 May 2008 earthquake. In comparison to the reference, the developed mapping approach could achieve over 80% accuracy for computation of the damage ratio. Future research is planned to test the approach on various disaster cases for both optical and radar images using a grid-computing platform towards a cost-effective damage mapping solution.

Place, publisher, year, edition, pages
2010. Vol. 31, no 13, 3411-3425 p.
Keyword [en]
National Category
Agricultural Science
URN: urn:nbn:se:kth:diva-29465DOI: 10.1080/01431161003727697ISI: 000280282000006ScopusID: 2-s2.0-77954849517OAI: diva2:395893

QC 20110208

Available from: 2011-02-08 Created: 2011-02-02 Last updated: 2016-04-20Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Vu, Tuong ThuyBan, Yifang
By organisation
Geoinformatics (closed 20110301)
In the same journal
International Journal of Remote Sensing
Agricultural Science

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 117 hits
ReferencesLink to record
Permanent link

Direct link