Abstract
Recently, web portals have been offering georeferenced SLI(Street-Level Imagery) services, such as Google Streetview. The SLI has a distinctive strength over aerial images or vector maps because it gives us the same view as we see the real world on the street. Based on the characteristic, applicability of the SLI can be increased substantially through conflation with other spatial datasets. However, spatial inconsistency between different datasets is the main reason to decrease the quality of conflation when conflating them. Therefore, this research aims to remove the spatial inconsistency to conflate an SLI with a widely used 2D vector map. The removal of the spatial inconsistency is conducted through three sub-processes of (1) road intersection matching between the SLI trace and the road layer of the vector map for detecting CPPs(Control Point Pairs), (2) inaccurate CPPs filtering by analyzing the trend of the CPPs, and (3) local alignment using accurate CPPs. In addition, we propose an evaluation method suitable for conflation result including an SLI, and verify the effect of the removal of the spatial inconsistency.
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