Share Email Print

Proceedings Paper

Obtaining accurate maps of topography and vegetation to improve 2D hydraulic flood models
Author(s): David M. Cobby; David C. Mason; Ian J. Davenport; Matthew S. Horritt
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Airborne scanning laser altimetry (LiDAR) is an important new data source for environmental applications, mapping topographic and surface object heights to high vertical and spatial accuracy over large areas. We present results of a segmentation system for LiDAR data for a reach of the river Severn, UK. The system has been developed to improve the 3 main data required by a leading numerical flood model predicting inundation extent, namely (i) a map of topographic height providing model bathymetry. A comparison with ground control points gives an accuracy of ±17cm (decreasing in the presence of steeply wooded slopes), (ii) the meandering location of the river channel and a suitable height contour which denote the extent of the model domain, and allow immediate finite element mesh generation, and (iii) a map of vegetation height (to an accuracy of ±14cm for grass and cereal crops) which is converted to friction coefficients. Errors due to overlapping swaths are significantly reduced. A 3-class segmentation of vegetation types (short, intermediate and tall) allows optimal height extraction algorithms to be separately applied, and enables realistic conversion to friction coefficients. Short (grass and cereal crops) and intermediate (hedges) vegetation are assumed to be flexible and either emergent or submerged during a flood cycle. Trees (tall vegetation) are modelled as rigid, emergent, stems.

Paper Details

Date Published: 23 January 2001
PDF: 12 pages
Proc. SPIE 4171, Remote Sensing for Agriculture, Ecosystems, and Hydrology II, (23 January 2001); doi: 10.1117/12.413925
Show Author Affiliations
David M. Cobby, Univ. of Reading (United Kingdom)
David C. Mason, Univ. of Reading (United Kingdom)
Ian J. Davenport, Univ. of Reading (United Kingdom)
Matthew S. Horritt, Univ. of Bristol (United Kingdom)

Published in SPIE Proceedings Vol. 4171:
Remote Sensing for Agriculture, Ecosystems, and Hydrology II
Manfred Owe; Guido D'Urso; Eugenio Zilioli, Editor(s)

© SPIE. Terms of Use
Back to Top