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Point Cloud Data Fusion for Enhancing 2D Urban Flood Modelling (Paperback)
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Point Cloud Data Fusion for Enhancing 2D Urban Flood Modelling (Paperback)
Series: IHE Delft PhD Thesis Series
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Modelling urban flood dynamics requires proper handling of a number
of complex urban features. Although high-resolution topographic
data can nowadays be obtained from aerial LiDAR surveys, such
top-view LiDAR data still have difficulties to represent some key
components of urban features. Incorrectly representing features
like underpasses through buildings or apparent blockage of flow by
sky trains may lead to misrepresentation of actual flood
propagation, which could easily result in inadequate
flood-protection measures. Hence proper handling of urban features
plays an important role in enhancing urban flood modelling. This
research explores present-day capabilities of using computer-based
environments to merge side-view Structure-from-Motion data
acquisition with top-view LiDAR data to create a novel multi-source
views (MSV) topographic representation for enhancing 2D model
schematizations. A new MSV topographic data environment was
explored for the city of Delft and compared with the conventional
top-view LiDAR approach. Based on the experience gained, the
effects of different topographic descriptions were explored for 2D
urban flood models of (i) Kuala Lumpur, Malaysia for the 2003 flood
event; and (ii) Ayutthaya, Thailand for the 2011 flood event. It
was observed that adopting the new MSV data as the basis for
describing the urban topography, the numerical simulations provide
a more realistic representation of complex urban flood dynamics,
thus enhancing conventional approaches and revealing specific
features like flood watermarks identification and helping to
develop improved flood-protection measures.
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