Remote sensing-based mapping of structural building damage in the Ahr valley

Abstract

Flood damage data are needed for various applications. Structural damage of buildings can reflect not only the economic damage but also the life-threatening condition of a building, which provide crucial information for disaster response and recovery. Since traditional on-site data collection shortly after a disaster is challenging, remote sensing data can be of great help, cover a wider area and be deployed earlier in time than on-site surveys. However, this has its challenges and limitations. We elucidate on that by presenting two case studies from flash floods in Germany. First, we assessed the reliability of an existing flood damage schema, which differentiates from minor (structural) damage to complete building collapse. We compared two on-site raters of the 2016 Braunsbach flood, reaching an excellent level of reliability. Second, we mapped structural building damage after the flood in the Ahr valley in 2021 using a textured 3D mesh and orthophotos. Here, we evaluated the remote sense-based damage mapping done by three raters. Although the heterogeneity of ratings using remote sensing data is larger than among on-site ratings, we consider it fit-for-purpose when compared with on-site mapping, especially for event documentation and as basis for financial damage estimation and less complex numerical modelling.