Exploiting qualitative spatial reasoning for topological adjustment of spatial data

• Authors: Jan Oliver Wallgrün
• Venue: Proceedings of the 20th International Conference on Advances in Geographic Information Systems
• Year: 2012

Formal models of spatial relations such as the 9-Intersection model or RCC-8 have become omnipresent in the spatial information sciences and play an important role to formulate constraints in many applications of spatial data processing. A fundamental problem in such applications is to adapt geometric data to satisfy certain relational constraints while minimizing the changes that need to be made to the data. We address the problem of adjusting geometric objects to meet the spatial relations from a qualitative spatial calculus, forming a bridge between the areas of qualitative spatial representation and reasoning (QSR) and of geometric adjustment using optimization approaches. In particular, we explore how constraint-based QSR techniques can be beneficially employed to improve the optimization process. We discuss three different ways in which QSR can be utilized and then focus on its application to reduce the complexity of the optimization problem in terms of variables and equations needed. We propose two constraint-based problem simplification algorithms and evaluate them experimentally. Our results demonstrate that exploiting QSR techniques indeed leads to a significant performance improvement.