1. Urban Building Damage Detection From Very High Resolution Imagery By One-Class SVM and Shadow Information Peijun Li, Benqin Song and Haiqing Xu Peking University, P. R. China Email: pjli@pku.edu.cn

3. Introduction Prompt and accurate detection of damage to urban infrastructure caused by disasters (e.g. earthquakes) Very high resolution satellite (VHR) images Automated detection and assessment methods: urgently required Fusion of different sensor data, use of single source data Existing methods (VHR optical data): mostly spectral data only, Objective : use of shadow change information to refine results

5. Flowchart of method Bitemporal images Bitemporal image segmentation Initial building damage detection: OCSVM Shadow and its change detection Result refinement Final result Accuracy assessment

7. Multilevel segmentation method (Multichannel watershed transformation + dynamics of contours) Li, P., Guo, J., Song, B. and Xiao, X., 2011, A multilevel hierarchical image segmentation method for urban impervious surface mapping using very high resolution imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 4(1), 103-116.

8. Initial building damage detection using OCSVM Building damage (‘building to non-building’): target class Multi-date composite classification: One-class Support Vector Machine (OCSVM) – one-class classifier

12. Study area: Dujianyan, China Datasets: Quickbird images (2005, 2008) Results

13. Initial building damage detection result Spectral data only

14. Shadow change information Black : shadow change White : no shadow change

15. Result comparison Building damage detection results by different methods (all in %) Damaged Undamaged OA Kappa PA UA PA UA Spectral only 69.63 66.41 84.82 86.63 80.25 53.71 Proposed method 63.73 84.75 95.06 84.44 85.88 63.25

16. Result comparison Spectral only Proposed method

17. Before After Spectral only Proposed method No damage Damage Result comparison

18. No damage Damage Before After Spectral only Proposed method Result comparison

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