Paper
23 January 2001 Obtaining accurate maps of topography and vegetation to improve 2D hydraulic flood models
David M. Cobby, David C. Mason, Ian J. Davenport, Matthew S. Horritt
Author Affiliations +
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.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David M. Cobby, David C. Mason, Ian J. Davenport, and Matthew S. Horritt "Obtaining accurate maps of topography and vegetation to improve 2D hydraulic flood models", Proc. SPIE 4171, Remote Sensing for Agriculture, Ecosystems, and Hydrology II, (23 January 2001); https://doi.org/10.1117/12.413925
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Cited by 6 scholarly publications.
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KEYWORDS
Vegetation

LIDAR

Floods

Data modeling

Chemical elements

Image segmentation

Bridges

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