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Zusammenfassung:
After large damaging earthquakes, fast and well-informed help efforts can save lives. The key information are the location and extent of damage and losses, in particular for disasters that affect large areas. Space-borne imaging methods, together with building-wise exposure data, can enable rapid damage assessments, delivering damage proxy maps for an entire affected region within hours. Space-borne damage proxy maps are generated e.g. from repeated synthetic aperture radar (SAR) imaging of the ground before and after an event to detect changes in the radar backscatter. Such changes are expressed in a drop of interferometric (InSAR) coherence. Dense human infrastructure, like building agglomerations, shows long-term stable backscatter characteristics and high coherence compared to many natural surfaces. Therefore, a sudden drop in coherence between pre- and post-earthquake images can be attributed to damage on the ground. However, without further information a detected damage tells little about the involved severity concerning human lives. Also, less dense settlement structures like villages may not show as long-term coherent areas and may not be included in damage maps even if strongly affected. Based on InSAR damage proxy maps from the 2023 Turkey Syria earthquakes, we present an approach to augment InSAR damage maps with information from exposure models combined with open building data. This combination can improve guiding rescue efforts by highlighting approximated damage with exposure models. Also, the building data help revealing blind spots in damage proxy maps, which are method-related, and should not go unnoticed.
