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Remote Sens. 2016, 8(7), 604; doi:10.3390/rs8070604

Flood Damage Analysis: First Floor Elevation Uncertainty Resulting from LiDAR-Derived Digital Surface Models

1
Department of Geological and Mining Engineering, University of Castilla-La Mancha (UCLM), Avda. Carlos III s/n, 45071 Toledo, Spain
2
Geoscience Research Department, Geological Survey of Spain (IGME), Ríos Rosas 23, 28003 Madrid, Spain
3
Institute for Water and Environmental Engineering (IIAMA), Department of Hydraulic Engineering and Environment, Technical University of Valencia (UPV), Camino de Vera s/n, 46022 Valencia, Spain
4
Department of Hydraulic Engineering and Environment, Technical University of Valencia (UPV), 46022 Valencia, Spain
*
Author to whom correspondence should be addressed.
Academic Editors: Magaly Koch, Lars T. Waser and Prasad S. Thenkabail
Received: 16 April 2016 / Revised: 21 June 2016 / Accepted: 11 July 2016 / Published: 19 July 2016
(This article belongs to the Special Issue Uncertainties in Remote Sensing)
View Full-Text   |   Download PDF [13833 KB, uploaded 19 July 2016]   |  

Abstract

The use of high resolution ground-based light detection and ranging (LiDAR) datasets provides spatial density and vertical precision for obtaining highly accurate Digital Surface Models (DSMs). As a result, the reliability of flood damage analysis has improved significantly, owing to the increased accuracy of hydrodynamic models. In addition, considerable error reduction has been achieved in the estimation of first floor elevation, which is a critical parameter for determining structural and content damages in buildings. However, as with any discrete measurement technique, LiDAR data contain object space ambiguities, especially in urban areas where the presence of buildings and the floodplain gives rise to a highly complex landscape that is largely corrected by using ancillary information based on the addition of breaklines to a triangulated irregular network (TIN). The present study provides a methodological approach for assessing uncertainty regarding first floor elevation. This is based on: (i) generation an urban TIN from LiDAR data with a density of 0.5 points·m−2, complemented with the river bathymetry obtained from a field survey with a density of 0.3 points·m−2. The TIN was subsequently improved by adding breaklines and was finally transformed to a raster with a spatial resolution of 2 m; (ii) implementation of a two-dimensional (2D) hydrodynamic model based on the 500-year flood return period. The high resolution DSM obtained in the previous step, facilitated addressing the modelling, since it represented suitable urban features influencing hydraulics (e.g., streets and buildings); and (iii) determination of first floor elevation uncertainty within the 500-year flood zone by performing Monte Carlo simulations based on geostatistics and 1997 control elevation points in order to assess error. Deviations in first floor elevation (average: 0.56 m and standard deviation: 0.33 m) show that this parameter has to be neatly characterized in order to obtain reliable assessments of flood damage assessments and implement realistic risk management. View Full-Text
Keywords: digital surface models (DSMs); urban features; breaklines; 2D hydraulic modelling; flood risk; Monte Carlo simulation; geostatistics digital surface models (DSMs); urban features; breaklines; 2D hydraulic modelling; flood risk; Monte Carlo simulation; geostatistics
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Bodoque, J.M.; Guardiola-Albert, C.; Aroca-Jiménez, E.; Eguibar, M.Á.; Martínez-Chenoll, M.L. Flood Damage Analysis: First Floor Elevation Uncertainty Resulting from LiDAR-Derived Digital Surface Models. Remote Sens. 2016, 8, 604.

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