Quality assessment of linear data

This paper presents methods to evaluate the geometric quality of spatial data. Firstly, a point-based method is presented, adapting conventional assessment methods whereby common points between datasets are compared. In our approach, initial matches are established automatically and refined further through interactive editing. Second, a line-based method which uses correspondences between line segments is proposed. Here, the geometry of line segments in vector is transformed into a set of rasterized values so that their combination at each pixel can restore their original vector geometry. Matching is performed on rasterized line segments and their matching lengths and displacements are measured. Experimental results show that the line-based approach proposed is efficient to evaluate the geometric quality of spatial data without requirements of topological relationships among line features.