Assessing building vulnerability using synergistically remote sensing and civil engineering

Abstract

The assessment of seismic building vulnerability depends on the quality of the information basis for the subject structures. Especially in dynamic and large megacities, information on the physical parameters of buildings is often generalized, outdated or simply unavailable. This study focuses on an interdisciplinary approach, using high resolution satellite data to infer dis-tinct building types for an up-to-date and area-wide coverage of the building stock. Physical parameters derived from IKONOS data describing the building stock are the height, the age and the roof type of the buildings. Referring to the available building classes, the capacity-spectrum method from civil engineering enables the country-specific adjustment of known vulnerability curves. The result is a spatial distribution of damage grades of various building types in the complex urban morphology. The synergistic use of remote sensing and civil engineering methods results in a more precise performance and a quantitative assessment of damage grades. A scenario, based on a simulated earthquake impact, enables the quantification of affected houses and affected people showing the capabilities to support disaster management before and shortly after an earthquake event.