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Discussion papers | Copyright
https://doi.org/10.5194/nhess-2018-158
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 29 Jun 2018

Research article | 29 Jun 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Flood depth estimation by means of high-resolution SAR images and LiDAR data

Fabio Cian1, Mattia Marconcini2, Pietro Ceccato3, and Carlo Giupponi1 Fabio Cian et al.
  • 1Department of Economics, University of Venice Ca' Foscari, Venice, 30121, Italy
  • 2DFD German Aerospace Center (DFD-DLR), Wessling, 82234, Germany
  • 3International Research Institute for Climate and Society (IRI), Columbia University, New York, USA

Abstract. When floods hit inhabited areas, great losses are usually registered both in terms of impacts on people (i.e., fatalities and injuries) as well as economic impacts on urban areas, commercial and productive sites, infrastructures and agriculture. To properly assess these, several parameters are needed among which flood depth is one of the most important as it governs the models used to compute damages in economic terms. This paper presents a simple yet effective semi-automatic approach for deriving very precise inundation depth. First, precise flood extent is derived employing a change detection approach based on the Normalized Difference Flood Index computed from high resolution Synthetic Aperture Radar imagery. Second, by means of a high-resolution Light Detection And Ranging Digital Elevation Model, water surface elevation is estimated through a statistical analysis of terrain elevation along the boundary lines of the identified flooded areas. Experimental results and quality assessment are given for the flood occurred in the Veneto region, North-Eastern Italy, in 2010. In particular, the method proved fast and robust and, compared to hydrodynamic models, it requires sensibly less input information.

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