Spatial phenomena in the real world can be stored in a set of spatial databases with different spatial shapes or scales. The set of spatial databases is called a multi-scale database. Deriving the multi-scale database automatically is important to response different user requests. Therefore, many researcher have studied in this area with various aspects.
One of the research areas is to assess the derivation results, and in this research, consistency assessment of the multi-scale database i9 considered. For the consistency assessment, two approaches are proposed in terms of a consistency of topological relationship and a derivation consistency.
First approach is to assess if or not, topological relationships derived respect original topological relationships based on set properties. In particular, the approach support that a multi-scale databases is derived by a collapse operator reducing dimension of a spatial object.
Second approach is dynamic update of a multi-scale database, which is to preserve derivation consistency between an original database and its derived database. The dynamic update supports to update parts of derived multi-scale data when its original objects are updated, instead of update the whole parts of the derived multi-scale database.
On a multi-scale database, the update of source occurs the update of its not only directly but also indirectly derived data. Besides, the update of source can be the cause of insert of new objects or delete of existing objects on the derived database. Without considering these update propagations, a derivation constraint of a multi-scale database can not be preserved.
The dynamic update approach proposed in this research provides a solution to handle these update propagation. We verified this approach by implementing on Windows 2000 with VC++ and Arc Objects library. This work contributes when multi-scale spatial data is serviced on a network or mobile environments, because light data are important for the environments to transfer or replace data.