Abstract
Detection and characterization of territorial elements exposed to flood is a key component for flood risk analysis. Land-use description works well for small scales of representation but it becomes too coarse while increasing the scale. “Single-element” characterization is usually achieved through surveys, which become prohibitive as the amount of elements to be characterized increases. Mapping schemes represent a compromise between level of description and efforts for data collection. The basic idea is to determine the statistical distribution of building characteristics inside a homogeneous class starting from a sample area and to apply this distribution to the whole area, realizing a statistical extrapolation. An innovative approach was developed, merging the mapping scheme methodologies developed by the Global Earthquake Model [1] and Blanco–Vogt and Schanze [2], in which homogeneous classes are not development areas but building clusters. The approach was applied to the buildings in the Bisagno River floodplain, Genoa (Italy). Buildings were classified according to a building taxonomy. Once the percentage of basement presence was assigned to each class by surveying a limited subset of the exposed assets, a series of possible basement distributions was simulated to calculate the corresponding damage distributions for a real flood event. The total average damage obtained is very close to the refund claims, with a percentage error lower than 2%.
Highlights
A natural hazard disaster risk is the intersection between a natural hazard and a certain human dimension, characterized by a certain exposure, a vulnerability and a resilience able to contain damage
Remote sensing is introduced as a powerful tool for exposure and vulnerability estimation, which can be synergistically integrated with data collected in-situ or through virtual surveys to obtain a description of the elements as complete as possible, in a way functional to properly apply vulnerability functions for damage estimation
Considering first of all the second of the two factors, we can argue that the propensity to suffer damage due to an external stress varies from building to building according to a series of structural and non-structural FKDUDFWHULVWLFV,W LV QHFHVVDU\ WR LQWURGXFH D 3VLQJOHHOHPHQW GHWDLOHG GHVFULSWLRQ RI H[SRVXUH LQ RUGHU WR properly model damage changes inside a certain land use homogeneous area
Summary
A natural hazard disaster risk is the intersection between a natural hazard and a certain human dimension, characterized by a certain exposure, a vulnerability and a resilience able to contain damage. The most general level of knowledge of the territory can be obtained using a land use map This type of information can be used as a starting point to evaluate how different territorial patterns respond to a certain hazard and to know a primary areal scale response of our study area. Remote sensing is introduced as a powerful tool for exposure and vulnerability estimation, which can be synergistically integrated with data collected in-situ or through virtual surveys to obtain a description of the elements as complete as possible, in a way functional to properly apply vulnerability functions for damage estimation. The systematic application of the methodology, starting from high-resolution optical data as input, will be tested through a study case based on a past event This choice will give us the opportunity to te.st the accuracy of the final results respect with both assets characterization and final damage evaluation
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