Preprints
https://doi.org/10.5194/nhess-2022-210
https://doi.org/10.5194/nhess-2022-210
 
30 Aug 2022
30 Aug 2022
Status: a revised version of this preprint was accepted for the journal NHESS and is expected to appear here in due course.

Bare-earth DEM Generation from ArcticDEM, and Its Use in Flood Simulation

Yinxue Liu, Paul Bates, and Jeffery Neal Yinxue Liu et al.
  • School of Geographical Sciences, University of Bristol, Bristol, UK

Abstract. In urban areas, topography data without above ground objects are typically preferred in wide-area flood simulation, but are not yet available for many locations globally. High-resolution satellite photogrammetry DEMs, like ArcticDEM, are now emerging and could prove extremely useful for global urban flood modelling, however approaches to generate bare-earth DEMs from them have not yet been fully investigated. In this paper, we test the use of two morphological filters (Simple Morphological Filter-SMRF and Progressive Morphological Filter-PMF) to remove surface artefacts from ArcticDEM using the city of Helsinki (192 km2) as a case study. The optimal filter is selected and used to generate a bare-earth version of ArcticDEM. Using a LIDAR DTM as a benchmark, the elevation error and flooding simulation performance for a pluvial event were then evaluated at 2 m and 10 m spatial resolution, respectively. The SMRF was found to be more effective at removing artefacts than PMF over a broad parameter range. For the optimal ArcticDEM-SMRF the elevation RMSE was reduced by up to 70 % over the uncorrected DEM, achieving a final value of 1.02 m. The simulated water depth error was reduced to 0.3 m, which is comparable to typical model errors using LIDAR DTM data. This paper indicates that the SMRF can be directly applied to generate a bare-earth version of ArcticDEM in urban environments, although caution should be exercised for areas with densely packed buildings or vegetation. The results imply that where LIDAR DTMs do not exist, widely available high-resolution satellite photogrammetry DEMs could be used instead.

Yinxue Liu et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2022-210', Dai Yamazaki, 21 Sep 2022
  • RC2: 'Comment on nhess-2022-210', Guy J.-P. Schumann, 06 Nov 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2022-210', Dai Yamazaki, 21 Sep 2022
  • RC2: 'Comment on nhess-2022-210', Guy J.-P. Schumann, 06 Nov 2022

Yinxue Liu et al.

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Short summary
In this paper, we test two approaches for removing buildings and other above-ground objects from a state-of-the-art satellite photogrammetry topography product, ArcticDEM. Our best technique gives a 70 % reduction in vertical error, with an average difference of 1.02 m from a benchmark LIDAR for the city of Helsinki in Finland. When used in a simulation of rainfall-driven flooding the bare-earth version of ArcticDEM yields a significant improvement in predicted inundation extent and water depth.
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