Spatiotemporal Indexing Mechanism Based on Snapshot-increment

Spatio-temporal index is one of the key technologies applied to spatio-temporal database engines. Methods for spatio-temporal indexes which consider efficiency of both temporal queries and spatial queries become hot topics in current research. In the versionincrement based spatio-temporal data model, “Version” is used to represent states of geographical phenomena, while “increment” changes of spatio-temporal phenomena based on version. The geometrical space in the version-increment spatio-temporal data model can’t be divided as it is the atom of space and time, and instead it can only change in forms of occurring, disappearing, replacing and so on. Occurring and disappearing are natures of changes, which can be integrated into basic types of spatio-temporal changes such as combination, division, replacement and so on. One feature may be changed in its geometrical space or attributes many times during its life-time. The geometrical space is considered as the primary atom of spatio-temporal index and it only has two changes during its life-time, with the first occurrence or replacing, the second disappearance or being replaced. The snapshot at any time is equal to the addition of the former snapshot and the increment between them. The amount of increment will grow larger and larger as time passes by, which makes it rather difficult to search for the increment between the version and some snapshot, thus there is a high demand for building spatiotemporal indexing mechanism based on increment. This paper proposes the versionincrement based spatiotemporal data model by abstracting existing spatiotemporal data models and put forward the snapshotincrement spatiotemporal indexing mechanism for this model. This mechanism takes both space and time as equally important dimensions and makes it able to perform quick searches based on time points and intervals, so efficiency of spatial and temporal queries are both concerned about.