SEMANTIC 3D CITY MODEL TO RASTER GENERALISATION FOR WATER RUN-OFF MODELLING
Keywords: Multi-scale modelling, water run-off modelling, 3D city models, semantic generalisation
Abstract. Water run-off modelling applied within urban areas requires an appropriate detailed surface model represented by a raster height grid. Accurate simulations at this scale level have to take into account small but important water barriers and flow channels given by the large-scale map definitions of buildings, street infrastructure, and other terrain objects. Thus, these 3D features have to be rasterised such that each cell represents the height of the object class as good as possible given the cell size limitations. Small grid cells will result in realistic run-off modelling but with unacceptable computation times; larger grid cells with averaged height values will result in less realistic run-off modelling but fast computation times. This paper introduces a height grid generalisation approach in which the surface characteristics that most influence the water run-off flow are preserved. The first step is to create a detailed surface model (1:1.000), combining high-density laser data with a detailed topographic base map. The topographic map objects are triangulated to a set of TIN-objects by taking into account the semantics of the different map object classes. These TIN objects are then rasterised to two grids with a 0.5m cell-spacing: one grid for the object class labels and the other for the TIN-interpolated height values. The next step is to generalise both raster grids to a lower resolution using a procedure that considers the class label of each cell and that of its neighbours. The results of this approach are tested and validated by water run-off model runs for different cellspaced height grids at a pilot area in Amersfoort (the Netherlands). Two national datasets were used in this study: the large scale Topographic Base map (BGT, map scale 1:1.000), and the National height model of the Netherlands AHN2 (10 points per square meter on average). Comparison between the original AHN2 height grid and the semantically enriched and then generalised height grids shows that water barriers are better preserved with the new method. This research confirms the idea that topographical information, mainly the boundary locations and object classes, can enrich the height grid for this hydrological application.