Seismic Risk Remote Sensing Exposure Modeling Disaggregation Techniques Earth Observation Earthquake Loss Estimation

External authors:

• Christian Geiss ( German Aerospace Centre (DLR) )
• Peter Priesmeier ( TH Koln Univ Appl Sci )
• Patrick Aravena Pelizari ( German Aerospace Centre (DLR) )
• Angelica Rocio Soto Calderon ( Technical University of Munich )
• Elisabeth Schoepfer ( German Aerospace Centre (DLR) )
• Torsten Riedlinger ( German Aerospace Centre (DLR) )
• Mabe Villar Vega ( IUSS PAVIA )
• Juan Camilo Gomez Zapata ( Helmholtz-Center Potsdam GFZ German Research Center for Geosciences , University of Potsdam )
• Massimiliano Pittore ( Helmholtz-Center Potsdam GFZ German Research Center for Geosciences , European Academy of Bozen-Bolzano )
• Emily So ( University of Cambridge )
• Alexander Fekete ( TH Koln Univ Appl Sci )
• Hannes Taubenboeck ( German Aerospace Centre (DLR) )

Abstract:

Exposure is an essential component of risk models and describes elements that are endangered by a hazard and susceptible to damage. The associated vulnerability characterizes the likelihood of experiencing damage (which can translate into losses) at a certain level of hazard intensity. Frequently, the compilation of exposure information is the costliest component (in terms of time and labor) of risk assessment procedures. Existing models often describe exposure in an aggregated manner, e.g., by relying on statistical/census data for given administrative entities. Nowadays, earth observation techniques allow the collection of spatially continuous information for large geographic areas while enabling a high geometric and temporal resolution. Consequently, we exploit measurements from the earth observation missions TanDEM-X and Sentinel-2, which collect data on a global scale, to characterize the built environment in terms of constituting morphologic properties, namely built-up density and height. Subsequently, we use this information to constrain existing exposure data in a spatial disaggregation approach. Thereby, we establish dasymetric methods for disaggregation. The results are presented for the city of Santiago de Chile, which is prone to natural hazards such as earthquakes. We present loss estimations due to seismic ground shaking and corresponding sensitivity as a function of the resolution properties of the exposure data used in the model. The experimental results underline the benefits of deploying modern earth observation technologies for refined exposure mapping and related earthquake loss estimation with enhanced accuracy properties.