Talks and Poster Presentations (with Proceedings-Entry):

G. Mandlburger, C. Briese:
"Using Airborne Laser Scanning for Improved Hydraulic Models";
Talk: International Congress on Modeling and Simulation - MODSIM07, Christchurch, New Zealand; 2007-12-10 - 2007-12-13; in: "Proceedings", (2007), ISBN: 978-09758400-4-7; 8 pages.

English abstract:
Due to recent flood events, risk assessment has
become a topic of highest public interest. The
definition of endangered or vulnerable areas is
based on numerical models of the water flow.
The most influential input for such models is the
topography provided as a Digital Terrain Model of the
Watercourse (DTM-W).
For capturing terrain data of inundation areas
Airborne Laser Scanning (ALS) has become the prime
data source. It combines cost efficiency, high degree
of automation, high point density of typically 1-10
points per m2 and good height accuracy of less than
15cm. For all these reasons ALS is particularly
suitable for deriving precise DTMs as basis for
Computational Fluid Dynamic (CFD) models. The
quality of such models depends crucially on how
well vegetation or other off-terrain objects have been
removed in the DTM generation process.
The task of removing off-terrain points from the
ALS measurements is commonly referred to as
filtering. Traditional laser scanners only supply
range measurements to the reflecting objects and,
thus, the filtering process has to rely on geometric
criteria. The latest generation of ALS systems
record the full backscattered waveform, from which
physical quantities like echo width and backscatter
cross section can be derived. An advanced filtering
technique based on the well established method of
robust interpolation is presented exploiting the echo
width for a more robust and reliable classification
of the point cloud into ground and off-terrain points
resulting in a more precise DTM-W. Besides filtering,
exact sensor calibration, fine adjustment of ALS-strip
data, proper fusion of ALS and additional river bed
data as well as elimination of random measurement
errors are important issues for generating a precise
DTM-W based on the ALS point cloud.
The higher DTM resolution provided by modern
sensors comes along with an increased amount of
data. Thus, a direct use of the high resolution
DTM-W as the geometric basis for CFD models is
impossible. Currently available mesh generators for
CFD models basically focus on physical parameters
of the calculation grid like angle criterion, aspect
ratio and expansion ratio. The detailed shape of
the terrain as provided by modern ALS systems is
often neglected. A DTM data reduction approach
is presented, considering both the physical aspects
mentioned above as well as the preservation of
relevant terrain details. The method starts with an
initial TIN-approximation of the DTM comprising
structure lines and a coarse grid. The TIN is
subsequently refined by adding additional grid points
until a certain height tolerance is met. A spatially
adaptive data density, where terrain parts being
sensitive for the CFD model are mapped with more
details than parts of minor importance, can be
achieved by introducing individual height tolerances
in the iterative refinement process. In order to obtain
a high quality computation grid the resulting surface
approximation is professionally conditioned to meet
specific hydraulic requirements.
Finally, practical results of CFD models based on different
geometry variants are presented and discussed.
It will be shown that a very detailed description of the
topography can indeed be established in CFD models,
resulting in more realistic flow simulations and more
precise boundaries of potential flooding areas.

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.