Building damage assessment after the earthquake in Haiti using two post-event satellite stereo imagery and DSMs

Abstract

In this article, a novel after-disaster building damage monitoring method is presented. This method combines the multispectral imagery and digital surface models (DSMs) from stereo matching of two dates to obtain three kinds of changes: collapsed buildings, newly built buildings and temporary shelters. The proposed method contains three basic steps. The first step is to focus on the DSMs and orthorectified images preparation. The second step is to segment the panchromatic images in obtaining small homogeneous regions. In the last step, a rule-based classification is built on the change information from iteratively reweighted multivariate alteration detection (IR-MAD) and height to extract the three kinds of changes. To further improve the accuracy of the results, a region-based grey-level co-occurrence matrix texture measurement is used. The proposed method is applied to monitor building changes after the 2010 Haiti earthquake, and the obtained results are further evaluated both visually and numerically.

Keywords:

• building damage
• change detection
• digital surface models
• segmentation

Acknowledgements

The authors would like to thank Dr Pablo d’Angelo for generating the DSMs and Dr Danielle Hoja for her work in data collection and preparation.