Simulation-based Building Change Detection from Multi-Angle SAR Images and Digital Surface Models

Abstract

This paper presents two change detection strategies based on the fusion of scene knowledge and two high resolution SAR images (pre-event, post-event) with focus on individual buildings and facades. Avoiding the dependence of the signal incidence angle, the methods increase the flexibility with respect to near-real-time SAR image analysis after unexpected events. Knowledge of the scene geometry is provided by digital surface models, which are integrated into an automated simulation processing chain. Using strategy 1 (based on building fill ratio; BFR), building changes are detected based on change-ratios considering layover and shadow areas. Strategy 2 (based on wall fill position; WFP) enables one to analyze individual facades of buildings without clear decision from strategy 1, which is based on a geometric projection of facade layover pixels. In a case study (Munich city center), the sensitivity of the change detection methods is exemplified with respect to destroyed buildings and partly changed buildings. The results confirm the significance of integrating prior knowledge from digital surface models into the analysis of high resolution SAR images.