Multi-resolution spatial query processing (2003–2005)

The cost of spatial query processing is directly related to spatial data complexity and accuracy. While spatial data is often stored in a database with the highest level of detail available, not all applications require the same level of detail. Recognising the difficulties of multiple representations of spatial data, in this project we propose to use multi-resolution data structures as a new foundation for efficient, application-dependent, on-demand derivation of data at different resolution levels. The systematic approach adopted in this project has the potential to deliver performance improvement that previous algorithm-level-only research cannot match. ''
Grant type:
ARC Discovery Projects
  • Professor
    School of Information Technology and Electrical Engineering
    Faculty of Engineering, Architecture and Information Technology
Funded by:
Australian Research Council