A data model and data structures for moving objects databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Modeling Spatial Relationships between 3D Objects
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
SQLST: a spatio-temporal data model and query language
ER'00 Proceedings of the 19th international conference on Conceptual modeling
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Multi-dimensional spatial data are obtained when a number of data acquisition devices are deployed at different locations to measure a certain set of attributes of the study subject. How to manipulate these spatial data remains a challenge to the database community, especially when the spatial locations are represented in 3D. In this work, we establish a data model to handle multi-dimensional spatial data with three spatial dimensions. In particular, firstly, a clustering algorithm is applied to group the data set into "point clouds". Secondly, each cloud is considered as a 3D spatial convex object and triangulated into a set of tetrahedrons. Thirdly, all tetrahedron sets are stored in the database and spatial analysis is performed. In this paper, we focus on defining 3D spatial operations and relationships for 3D spatial elements (points, segments, triangles and tetrahedrons), and further applying these operations on 3D spatial objects, where each object is composed of a set of tetrahedrons.