Abstract
The modeling of flood damage is an important component for risk analyses, which are the basis for risk-oriented flood management, risk mapping, and financial appraisals. An automatic urban structure type mapping approach was applied on a land use/land cover classification generated from multispectral Ikonos data and LiDAR (Light Detection And Ranging) data in order to provide spatially detailed information about the building stock of the case study area of Dresden, Germany. The multi-parameter damage models FLEMOps (Flood Loss Estimation Model for the private sector) and regression-tree models have been adapted to the information derived from remote sensing data and were applied on the basis of the urban structure map. To evaluate this approach, which is suitable for risk analyses, as well as for post-disaster event analyses, an estimation of the flood losses caused by the Elbe flood in 2002 was undertaken. The urban structure mapping approach delivered a map with a good accuracy of 74% and on this basis modeled flood losses for the Elbe flood in 2002 in Dresden were in the same order of magnitude as official damage data. It has been shown that single-family houses suffered significantly higher damages than other urban structure types. Consequently, information on their specific location might significantly improve damage modeling, which indicates a high potential of remote sensing methods to further improve risk assessments.
Highlights
Increasing frequency and intensity of floods, as well as a high settlement density and associated concentration of valuable objects in flood-prone areas, are the central causes of increasing economic losses through extreme events [1]
This study demonstrated how remote sensing data can be used in order to improve flood loss estimation for risk analyses, due to providing detailed spatial information on different residential building types which was not available before
An urban structure mapping approach was applied based on multispectral remote sensing data and LiDAR data to obtain information about the building stock and their characteristics
Summary
Increasing frequency and intensity of floods, as well as a high settlement density and associated concentration of valuable objects in flood-prone areas, are the central causes of increasing economic losses through extreme events [1]. An integrated risk-based flood management includes engineering systems (structural measures), and precaution (e.g., flood-adapted building construction, risk adapted land use planning, early warning system) and water retention in the catchment (e.g., land use management in upstream basins) [1]. In this context, flood risk is understood as the probability of the occurrence of losses caused by a flood scenario within a certain time, considering the hazard (return period of the flood, extent and inundation depth) and vulnerability (exposure of people and assets to floods and their susceptibility) [6]. An efficient risk management requires a detailed risk assessment, combining information about the components flood hazard, exposure (e.g., land use and value of elements at risk), and susceptibility of the elements at risk to hydrologic conditions (e.g., depth–damage curves) [7]
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