Abstract
Abstract. In this paper various schemes for visualizing geo-spatial data such as Computational Fluid Dynamics (CFD) data are explored. The architecture of a new Smart Cities Platform is presented and examples of the visualization capabilities are given. Results show that scalar and vectorial measurands, such as wind pressure and wind directions, may be presented using the same schemes, however, interpretation of the visualization varies between measurands. A hex-grid representation of the highly dense point cloud data yields easier interpretation of the scene as do streamlines for visualizing a path of flow over and around buildings. Results of performance evaluations suggest that the same visualisation scheme (e.g. hex-grid) but different data formats, yields faster loading times when using 3D Tiles rather than GeoJSON and an overall smoother interaction within the application.
Highlights
Just like companies and organizations, modern cities are facing the age of digital transformation towards smarter cities
For Computational Fluid Dynamics (CFD) simulations in cities as well as visualization of buildings in 3D, CityGML models serve as a basis prior to conversion into appropriate CAD file formats (e.g. STEP) and streamable tile formats (e.g. 3DTiles, Cozzi et al 2019), respectively
The use of CityGML data for CFD simulations is problematic because of errors and the complexity of building models leading to high computational demands, steps for simplifications need to be done; this is beyond the scope of this paper
Summary
Just like companies and organizations, modern cities are facing the age of digital transformation towards smarter cities. With modern rendering capabilities and definition of OGC standards (Open Geospatial Consortium) for defining rendering pipelines, streamable formats and web standards, the technical hurdles to implementing powerful data visualizations is streamlined as never before. This allows, to show highly heterogeneous data in a single view, render large data sets at high frame rates and even deliver relatively large and complex data sets at low bandwidth speeds due to streamable formats The double-blind peer-review was conducted on the basis of the full paper
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