Quality Inspection and Quality Improvement by Map Fusion

In this paper a new approach for quality measurement and improvement using map matching and map fusion is introduced. In the first part we describe a matching model based on “Buffer growing”. The matching, which is the basis for the quality inspection and the map fusion, is performed manually with a tool developed with VBA and ArcGIS. The quality inspection can be subdivided into a global and a local quality inspection. A global quality measure indicates the similarity of two datasets whereas a local quality measure indicates the similarity of a single matching pair. In the second part of the paper we introduce a method for the fusion of two datasets. The objects in one dataset are used as basis data. The unmatched objects of the other dataset have to be transferred into the basis dataset. In order to realize our approach, all unmatched objects are allocated in clusters. Then, linking nodes are searched in both datasets. The unmatched objects in the cluster are transferred into the basic dataset using a 2-parameter, 4-parameter or 6parameter transformation.