Positioning localities based on spatial assertions
In practice, descriptive localities are often communicated using named places and spatial relationships. Uncertainty associated with such descriptions of localities is inevitable, and knowledge of such uncertainty is normally not explicit. When translating descriptive localities into spatially explicit ones, it is critical to circumscribe locations and to estimate the associated uncertainty based on a set of appropriate spatial relationships. In conventional research on qualitative spatial reasoning (QSR), spatial relationships are modeled using formal logic. Unfortunately, QSR cannot deal with the uncertainty of a position. In this paper, based on the conceptual model of spatial assertions, we introduce the uncertainty field model to represent the probability distribution of a point locality. Using probability operations, we can combine a set of assertions to position a locality. Conflicts among assertions for a single locality can be detected based on the resulting field. Since spatial relationships play an important role in the uncertainty of target objects, we investigate conceptually the uncertainty fields associated with various types of spatial relationships (for example, topological, directional and metric). In a concrete application, these uncertainty fields can be customized and used without altering the proposed framework.
spatial relationship uncertainty field probability geographic information system spatial positioning