Road network selection for small-scale maps using an improved centrality-based algorithm

The road network is one of the key feature classes in topographic maps and databases. In the task of deriving road networks for products at smaller scales, road network selection forms a prerequisite for all other generalization operators, and is thus a fundamental operation in the overall process o...

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Main Authors: Roy Weiss, Robert Weibel
Format: Article
Language:English
Published: University of Maine 2014-12-01
Series:Journal of Spatial Information Science
Subjects:
Online Access:http://josis.org/index.php/josis/article/view/166
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spelling doaj-c97589a2cf40438eb0bac258bdd666632020-11-24T22:38:45ZengUniversity of MaineJournal of Spatial Information Science1948-660X2014-12-0120149719910.5311/JOSIS.2014.9.166104Road network selection for small-scale maps using an improved centrality-based algorithmRoy Weiss0Robert Weibel1University of Zurich, Department of GeographyUniversity of Zurich, Department of GeographyThe road network is one of the key feature classes in topographic maps and databases. In the task of deriving road networks for products at smaller scales, road network selection forms a prerequisite for all other generalization operators, and is thus a fundamental operation in the overall process of topographic map and database production. The objective of this work was to develop an algorithm for automated road network selection from a large-scale (1:10,000) to a small-scale database (1:200,000). The project was pursued in collaboration with swisstopo, the national mapping agency of Switzerland, with generic mapping requirements in mind. Preliminary experiments suggested that a selection algorithm based on betweenness centrality performed best for this purpose, yet also exposed problems. The main contribution of this paper thus consists of four extensions that address deficiencies of the basic centrality-based algorithm and lead to a significant improvement of the results. The first two extensions improve the formation of strokes concatenating the road segments, which is crucial since strokes provide the foundation upon which the network centrality measure is computed. Thus, the first extension ensures that roundabouts are detected and collapsed, thus avoiding interruptions of strokes by roundabouts, while the second introduces additional semantics in the process of stroke formation, allowing longer and more plausible strokes to built. The third extension detects areas of high road density (i.e., urban areas) using density-based clustering and then locally increases the threshold of the centrality measure used to select road segments, such that more thinning takes place in those areas. Finally, since the basic algorithm tends to create dead-ends—which however are not tolerated in small-scale maps—the fourth extension reconnects these dead-ends to the main network, searching for the best path in the main heading of the dead-end.http://josis.org/index.php/josis/article/view/166map generalizationroad network selectionstrokesnetwork centralitybetweenness centrality
collection DOAJ
language English
format Article
sources DOAJ
author Roy Weiss
Robert Weibel
spellingShingle Roy Weiss
Robert Weibel
Road network selection for small-scale maps using an improved centrality-based algorithm
Journal of Spatial Information Science
map generalization
road network selection
strokes
network centrality
betweenness centrality
author_facet Roy Weiss
Robert Weibel
author_sort Roy Weiss
title Road network selection for small-scale maps using an improved centrality-based algorithm
title_short Road network selection for small-scale maps using an improved centrality-based algorithm
title_full Road network selection for small-scale maps using an improved centrality-based algorithm
title_fullStr Road network selection for small-scale maps using an improved centrality-based algorithm
title_full_unstemmed Road network selection for small-scale maps using an improved centrality-based algorithm
title_sort road network selection for small-scale maps using an improved centrality-based algorithm
publisher University of Maine
series Journal of Spatial Information Science
issn 1948-660X
publishDate 2014-12-01
description The road network is one of the key feature classes in topographic maps and databases. In the task of deriving road networks for products at smaller scales, road network selection forms a prerequisite for all other generalization operators, and is thus a fundamental operation in the overall process of topographic map and database production. The objective of this work was to develop an algorithm for automated road network selection from a large-scale (1:10,000) to a small-scale database (1:200,000). The project was pursued in collaboration with swisstopo, the national mapping agency of Switzerland, with generic mapping requirements in mind. Preliminary experiments suggested that a selection algorithm based on betweenness centrality performed best for this purpose, yet also exposed problems. The main contribution of this paper thus consists of four extensions that address deficiencies of the basic centrality-based algorithm and lead to a significant improvement of the results. The first two extensions improve the formation of strokes concatenating the road segments, which is crucial since strokes provide the foundation upon which the network centrality measure is computed. Thus, the first extension ensures that roundabouts are detected and collapsed, thus avoiding interruptions of strokes by roundabouts, while the second introduces additional semantics in the process of stroke formation, allowing longer and more plausible strokes to built. The third extension detects areas of high road density (i.e., urban areas) using density-based clustering and then locally increases the threshold of the centrality measure used to select road segments, such that more thinning takes place in those areas. Finally, since the basic algorithm tends to create dead-ends—which however are not tolerated in small-scale maps—the fourth extension reconnects these dead-ends to the main network, searching for the best path in the main heading of the dead-end.
topic map generalization
road network selection
strokes
network centrality
betweenness centrality
url http://josis.org/index.php/josis/article/view/166
work_keys_str_mv AT royweiss roadnetworkselectionforsmallscalemapsusinganimprovedcentralitybasedalgorithm
AT robertweibel roadnetworkselectionforsmallscalemapsusinganimprovedcentralitybasedalgorithm
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