Object Oriented Change Detection of Rectangular Buildings after the Indian Ocean Tsunami Disaster

The tsunami of December 26, 2004 was one of the worst disasters in human history. Following a disaster, change detection is a prerequisite for quick assessments of damage. To assess the severity of devastation, most damage assessments focus on the destruction of man-made objects, particularly buildings.

In this work, we develop a robust rectangular building detection that can detect both small-size buildings in residential areas and large-size buildings in industrial areas. We use both edge detection and region growing approaches to supplement each other. The discovered buildings then become the inputs to our change detection. We employ knowledge based intelligent agents to recognize buildings before and after a disaster. The figure below presents the overview of the system implementation.

The figure below discusses the rectangular building extraction procedure which is a two-step process: 1) Edge detection by Canny detector, 2) Region growing.

The picture below presents the building candidates.

Specifying classification rules into the object-based change detection system, the detected changes are presented below:

Publications:
1. Tanathong, S., Rudahl, K.T., Goldin, S.E., 2009. Object oriented change detection of buildings after a disaster. Proceedings of ASPRS, Baltimore, USA. [PDF]
2. Tanathong, S., Rudahl, K.T., Goldin, S.E., 2008. Object oriented change detection of buildings after the Indian Ocean tsunami disaster. Proceedings of ECTI-CON, Krabi, Thailand. [PDF][LINK]
3. Tanathong, S., Rudahl, K.T., Goldin, S.E., 2007. Object-based change detection: the tsunami disaster case. Proceedings of ACRS, Kuala Lumpur, Malaysia. [PDF]