A qualitive reasoning approach for improving query results for sketch based queries by topological analysis of spatial aggregation

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.Sketch-based spatial query systems provide an intuitive method of user interaction for spatial databases. These systems must be capable of interpreting user sketches in a way that matches the information that the user intended to provide. One challenge that must be overcome is that humans always simplify the environments they have experienced and this is reflected in the sketches they draw. One such simplification is manifested as aggregation or combination of spatial objects into conceptually or spatially related groups. In this thesis I develop a system that uses reasoning tools of the RCC-8 to evaluate sketchbased queries and provide a method for minimizing the effects of aggregation by determining whether a solution to a query can be expanded if some groups of regions are assumed to be parts of a larger aggregate region. If such a group of regions is found, then this group must be included in the solution. The solution is approximate because the approach taken only verifies that assumed parts of an aggregate are not inconsistent with the configuration of the whole solution. Only cases where the size of the solution equals the size of the query minus one are analysed. It is observed that correctly identifying aggregated regions leads to solutions that are more similar to the original query sketch when the size of every other solution is smaller than the size of the query or when a lower limit is placed on the acceptable size of a solution because the new, expanded or refined solution becomes more complete with respect to the sketch of the query

Cognitively plausible representations for the alignment of sketch and geo-referenced maps

In many geo-spatial applications, freehand sketch maps are considered as an intuitive way to collect user-generated spatial information. The task of automatically mapping information from such hand-drawn sketch maps to geo-referenced maps is known as the alignment task. Researchers have proposed various qualitative representations to capture distorted and generalized spatial information in sketch maps, however thus far the effectiveness of these representations has not been evaluated in the context of an alignment task. This paper empirically evaluates a set of cognitively plausible representations for alignment using real sketch maps collected from two different study areas with the corresponding geo-referenced maps. Firstly, the representations are evaluated in a single-aspect alignment approach by demonstrating the alignment of maps for each individual sketch aspect. Secondly, representations are evaluated across multiple sketch aspects using more than one representation in the alignment task. The evaluations demonstrated the suitability of the chosen representation for aligning user-generated content with geo-referenced maps in a real-world scenario