Point cloud data fusion for enhancing 2D urban flood modelling (1st)

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 schematisations.