Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/nhess-2017-93
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
27 Mar 2017
Review status
This discussion paper is under review for the journal Natural Hazards and Earth System Sciences (NHESS).
Direct local building inundation depth determination in 3D point clouds generated from user-generated flood images
Luisa Griesbaum1, Sabrina Marx1, and Bernhard Höfle1,2 1GIScience, Department of Geography, Heidelberg University, Heidelberg, 69120, Germany
2Heidelberg Center for the Environment (HCE), Heidelberg University, 69120 Heidelberg, Germany
Abstract. In recent years, the number of people affected by flooding caused by extreme weather events has increased considerably. In order to provide support in disaster recovery or to develop mitigation plans, accurate flood information is necessary. Particularly pluvial urban floods, characterized by high temporal and spatial variations, are not well documented. This study proposes a new, low-cost approach to determining local flood elevation and inundation depth of buildings based on user-generated flood images. It first applies close-range digital photogrammetry to generate a geo-referenced 3D point cloud. Second, based on estimated camera orientation parameters, the flood level captured in a single flood image is mapped to the previously derived point cloud. The local flood elevation and the building inundation depth can then be derived automatically from the point cloud. The proposed method is carried out once for each of 66 different flood images showing the same building façade. An overall accuracy of 0.05 m  with an uncertainty of ±0.13 m for the derived flood elevation within the area of interest and an accuracy of 0.13 m  ± 0.10 m for the determined building inundation depth is achieved. Our results demonstrate that the proposed method can provide reliable flood information on a local scale using user-generated flood images as input. The approach can thus allow inundation depth maps to be derived even in complex urban environments with relatively high accuracies.

Citation: Griesbaum, L., Marx, S., and Höfle, B.: Direct local building inundation depth determination in 3D point clouds generated from user-generated flood images, Nat. Hazards Earth Syst. Sci. Discuss., doi:10.5194/nhess-2017-93, in review, 2017.
Luisa Griesbaum et al.
Luisa Griesbaum et al.
Luisa Griesbaum et al.

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