Digital 3D city models play a crucial role in research of urban phenomena; they form the basis for flow simulations, urban planning, and analysis of underground formations. Urban scenes consist of large collections of semantically rich objects which have a large number of properties such as material and colour. Modelling and storing these properties indicating the relationships between them is best handled in a relational databases. Our goal is to have a spatial DBMS which iteratively loads data from different sources and converts it into a common format to enable 3D operations and analyses, such as 3D intersections, and semantic properties management.
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Conference eScience Symposium
Citation
Goncalves, R.A, Ivanova, M.G, Kersten, M.L, Scholten, H, Zlatanova, S, Alvanaki, F, … Dias, E. (2014). Big Data analytics in the Geo-Spatial Domain. In Proceedings of 2nd eScience Symposium 2014 (0).