In this paper we propose to treat point clouds as a first-class representation (similar to vector or raster representations), with the nD-PointCloud as the solution for this, offering deep integration of space, time and scale. For efficiency rea-sons spatial indexing and clustering of these large point clouds is extremely important and this is obtained based on a Space Filling Curved (SFC). In order to get beyond the current state of the art of storing/ managing point clouds in files, a DBMS solution is presented (with all benefits: integration with other data types, scalability, multi-user, transaction support, etc.). Finally, a DBMS SFC interface specification for point clouds is proposed.
|Title of host publication||Geoinformationssysteme 2019, Beiträge zur 6. Münchner GI-Runde|
|Editors||Thomas Kolbe, Ralf Bill, Andreas Donaubauer|
|Place of Publication||München|
|Publisher||Runder Tisch GIS|
|Number of pages||11|
|Publication status||Published - 2019|
|Event||Münchner GI-Runde 2019 - München, Germany|
Duration: 14 Mar 2019 → 15 Mar 2019
|Conference||Münchner GI-Runde 2019|
|Period||14/03/19 → 15/03/19|
Oosterom, P. V., Meijers, M., Verbree, E., Liu, H., & Tijssen, T. (2019). Towards a relational database Space Filling Curve (SFC) interface specification for managing nD-PointClouds. In T. Kolbe, R. Bill, & A. Donaubauer (Eds.), Geoinformationssysteme 2019, Beiträge zur 6. Münchner GI-Runde (pp. 61-71). Runder Tisch GIS.