Creating Dynamic 3D City Models for Smarter Cities

The project will investigate the algorithms required to produce multi-purpose, generalised 3D maps, taking
into account the multiple levels of detail required when navigating around a 3D scene. The research combines
two aspects of the generalisation problem - research into algorithms required to generalise 3D datasets and
research into potential users of these generalised datasets. This is fundamental as it can be hypothesized that
in 3D generalisation, as with 2D generalisation, decisions taken through the process (exaggeration,
simplification, amalgamation and so forth) are heavily dependent on the end use of the resulting dataset.
Additionally, as noted above, unlike 2D, in a 3D context there is not one 'final' scale equally applicable across
an entire dataset. The work focusses on outdoor generalisation specifically, starting at the building and
moving out to the city.
Research questions include:
1. The clarification of user requirements for generalised 3D data- e.g. which features need to be
emphasized, how important is maintaining topological relationship. This may be done on a use-case
specific basis - i.e. by identifying real world examples
2. How can the required generalisation algorithms (computational geometry) be developed?
3. Would the use of point-cloud simplification be of benefit to 3D generalisation?
4. Investigating on-the-fly generalization.