Big Data analytics in the Geo-Spatial Domain

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.