Research Of The Identical Entity Matching Of Vector Map Edge Matching

In order to improve the reuse of land use data, reduce the costs of dataacquisition, speed up the update process of land use data, it is required to makeintegration and information fusion of spatial data which have various scales andcross different departments, trades, regions and time phases. For themanagement and analysis of large area spatial data, edge matching is the mostbasic step. Only remove the combined errors of boundary elements in adjacentmap sheets and piece together all small area maps into a complete map, we cancarry on the follow-up integration work such as superposition matching. In thespatial data of map merging, identical entity matching is one of the keytechnologies. At home and abroad, there have many researches and applicationsabout the identical entity matching, especially, the most commonly used methodof geometric matching. However, the existing geometric matching methods arebased on measuring the "two-two distance" between a selected element andother elements in adjacent map sheet. When the number of boundary elements islarge, the large amount of distance calculation always caused the low programefficiency. Some GIS software has edge merging module, but these modulesoften require a lot of manual involvement and have a lot of work and a lowerdegree of automation. Therefore, the development of an efficient automatic edgematching system has great practical significance to improve the efficiency ofmap edge merging. In this paper, we selected the divided boundary elements in adjacent mapsthrough spatial query and overlay analysis. Focus on the geometric matchingtechnology of line features and area features. According to the original methoddepends on the frequent distance measurement between endpoint, this paper putforward to use a circular area buffer to obtain the candidate matching elementsthat are near with the selected element. And on this basis, increased trendmatching to improve the accuracy of geometric matching and reduce theworkload of the follow-up property matching. Finally, the algorithm is appliedto the intelligent edge merging processing system to achieve an automaticregional multi-map merging. The main works are as follows:1. Analyzed the characteristics of spatial data, especially for the datastructure of vector spatial data. Discussed the sources of combined error of point,area and line feature which near the boundary of map, and studied thepreprocessing methods of the consistency of data before edge merging.Analyzed the process of map merging and identical entity matching.2. Studied the process of geometric matching of point, line and area feature,according to the inadequacies of the existing matching methods：distancecalculation was large and matching index was single, proposed line features’circular region fitting matching method and area features’ secant-midpointdistance matching method, and conducted experiments on actual data. Theresults show that the improved method can effectively improve the efficiency ofgeometric matching, reduce the workload of the properties matching.3. Designed an intelligent system of land use data edge-matchingprocessing. It developed by ArcGIS Engine and Visual Studio2010, andachieved the improved geometric matching method, we can import all maps atonce. The merge process had less manual intervention and after the matching itcan show the statistical results of matching, it also can be manually modified.This system not only can be put into actual production as a separate edge merge software, but also as a subsystem of the optimization and transformation systemof land use history database.