Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회지)

Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회)
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Generalization of Road Network using Logistic Regression

  • Park, Woojin (Seoul Institute of Technology) ;
  • Huh, Yong (Korea Research Institute for Human Settlements)
  • Received : 2019.04.09
  • Accepted : 2019.04.26
  • Published : 2019.04.30
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Abstract

In automatic map generalization, the formalization of cartographic principles is important. This study proposes and evaluates the selection method for road network generalization that analyzes existing maps using reverse engineering and formalizes the selection rules for the road network. Existing maps with a 1:5,000 scale and a 1:25,000 scale are compared, and the criteria for selection of the road network data and the relative importance of each network object are determined and analyzed using $T{\ddot{o}}pfer^{\prime}s$ Radical Law as well as the logistic regression model. The selection model derived from the analysis result is applied to the test data, and road network data for the 1:25,000 scale map are generated from the digital topographic map on a 1:5,000 scale. The selected road network is compared with the existing road network data on the 1:25,000 scale for a qualitative and quantitative evaluation. The result indicates that more than 80% of road objects are matched to existing data.

Keywords

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Fig. 1. Workflow of this study

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Fig. 2. Extraction process for matching pair of road centerlines between different scales

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Fig. 3. Road centerline of digital topographic map at 1:5,000 (left) and 1:25,000 (right) scale for target area of training data (all over Giheung-gu, Yongin-si)

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Fig. 4. Histogram of SPF value for road network of test data

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Fig. 5. Threshold estimation using total length of target line, the cumulative function of SPF and length of line

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Fig. 7. An example of the discrepancy caused by gaps in the method that expresses a dual line as a single line (the matched line (black) and commission error (gray) of the proposed method)

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Fig. 8. An example of the discrepancy caused by excessively expressed small road centerlines (the matched line (black) and commission error (gray) of the proposed method)

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Fig. 6. An example of the discrepancy caused by gaps in the update period (the matched line (black) and commission error (gray) of the proposed method, The vertical road in the middle: a road object that was inserted after renewal of the NGII digital map)

Table 1. Attribute schema of reconstructed road centerline data

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Table 2. Total length of the road network for the matching results between the selected road centreline from the two methods and the NGII map data

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