[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.7848/ksgpc.2019.37.2.91

Generalization of Road Network using Logistic Regression

Park, Woojin (Seoul Institute of Technology)
Huh, Yong (Korea Research Institute for Human Settlements)

Publication Information

Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.37, no.2, 2019 , pp. 91-97 More about this Journal

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

Road Network; Map Generalization; Selection and Elimination; Radical Law; Logistic Regression Model;

Citations & Related Records

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