The consequences of recent floods and flash floods in many parts of
the world have been devastating. One way to improving flood
management practice is to invest in data collection and modelling
activities which enable an understanding of the functioning of a
system and the selection of optimal mitigation measures. A Digital
Terrain Model (DTM) provides the most essential information for
flood managers. Light Detection and Ranging (LiDAR) surveys which
enable the capture of spot heights at a spacing of 0.5m to 5m with
a horizontal accuracy of 0.3m and a vertical accuracy of 0.15m can
be used to develop high accuracy DTM but needs careful processing
before using it for any application.This book presents the
augmentation of an existing Progressive Morphological filtering
algorithm for processing raw LiDAR data to support a 1D/2D urban
flood modelling framework. The key characteristics of this improved
algorithm are: (1) the ability to deal with different kinds of
buildings; (2) the ability to detect elevated road/rail lines and
represent them in accordance to the reality; (3) the ability to
deal with bridges and riverbanks; and (4) the ability to recover
curbs and the use of appropriated roughness coefficient of
Manning's value to represent close-to-earth vegetation (e.g. grass
and small bush).
General
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