• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.459-467
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• 2014

The importance of fusion and association using established spatial information has increased gradually with the production and supply of various spatial data by public institutions. The generation of necessary spatial information without field investigation and additional surveying can reduce time, labor, and financial costs. However, the study of the integration of the newly introduced road name address map with the digital map is very insufficient. Even though the use of the road name address map is encouraged for public works related to spatial information, the digital map is still widely used because it is the national basic map. Therefore, in this study, building matching and update were performed to associate the digital map with the road name address map. After geometric calibration using the block-based ICP (Iterative Closest Point) method, multi-scale corresponding pair searching with hierarchical clustering was applied to detect the multi-type match. The accuracy assessment showed that the proposed method is more than 95% accurate and the matched building layer of the two maps is useful for the integrated application and fusion. In addition, the use of the road name address map, which carries the latest and most frequently renewed data, enables cost-effective updating of new buildings.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.99-106
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• 2019

Technology that cannot be excluded from 4th industry is self-driving sector. The self-driving sector can be seen as a key set of technologies in the fourth industry, especially in the DB sector is getting more and more popular as a business. The DB, which was previously produced and managed in two dimensions, is now evolving into three dimensions. Among the data obtained by Mobile Mapping System () to produce the HD MAP necessary for self-driving, Point Cloud, which is LiDAR data, is used as a DB because it contains accurate location information. However, at present, it is not widely used as a base data for 3D modeling in addition to HD MAP production. In this study, MMS Point Cloud was used to extract facilities around the road and to overlay the location to expand the usability of Point Cloud. Building utility poles and communication poles DB from Point Cloud and comparing road name address base and location, it is believed that the accuracy of the location of the facility DB extracted from Point Cloud is also higher than the basic road name address of the road, It is necessary to study the expansion of the facility field sufficiently.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.1
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• pp.45-52
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• 2015

The interoperability of multi-source data has become more important due to various digital maps, produced from public institutions and enterprises. In this study, the automatic matching algorithm of multi-source building data using hierarchical matching was proposed. At first, we divide digital maps into blocks and perform the primary geometric registration of buildings with the ICP algorithm. Then, corresponding building pairs were determined by evaluating the similarity of overlap area, and the matching threshold value of similarity was automatically derived by the Otsu binary thresholding. After the first matching, we extracted error matching candidates buildings which are similar with threshold value to conduct the secondary ICP matching and to make a matching decision using turning angle function analysis. For the evaluation, the proposed method was applied to representative public digital maps, road name address map and digital topographic map 2.0. As a result, the F measures of matching and non-matching buildings increased by 2% and 17%, respectively. Therefore, the proposed method is efficient for the matching of building polygons from multi-source digital maps.