The showcase exemplifies how IQmulus could respond to the requirements and expectations of expert users (typically hydrologists or geologists) supporting decision makers in civil protection in events related to flooding. The goal is to demonstrate the usefulness of IQmulus to compute rapidly, even roughly, parameters needed to run flooding simulation or landslide models.

A number of the marine workflows are based on a new approach for surface representation called Locally Refined B-splines (LR B-splines). In IQmulus LR B-splines approximation/regression methods have been developed for geospatial big data, allowing millions of points to be approximated by a locally refined spline surface. This is a major innovation compared to traditional multivariate spline approximations/regression methods that a tensor product approach refinements of the representation leads to an explosion in data volume of the representation. The LR B-splines refinements only add degrees of freedom locally when needed, and consequently the storage footprint is kept low. For ocean floors and sea beds that have a large smooth areas we have observed a reduction of data volume by two orders of magnitude. By sampling the resulting surface traditional surface representation such as GeoTIFF can be generated and the sampled points used as input to other workflows.

Given a new data set a cartography expert is tasked with the update of an existing 3D catalogue of urban topographic objects, such as the detection of buildings for monitoring and cadastral updating or individual tree extraction from urban LMMS (Laser Mobile Mapping Systems) data.