SOLAP based on novel spatial dimensions

Abstract

The ratio of spatial dimensions to all dimensions in data cube is very small, and spatial dimensions do not contain a wealth of spatial information, all these become a bottleneck of current space online analytical processing (SOLAP). Aiming at these problems, this paper proposed a new method to build novel dimensions, auxiliary spatial dimensions. With the help of SQDL-G, relationships between central theme and neighborhood objects are introduced into the new spatial dimensions, and data cube will contain more spatial information. The case study demonstrates that this method makes full use of topological operations, quantifies spatial relationship, and promotes the analytical capacity of SOLAP. © Springer-Verlag Berlin Heidelberg 2012.