Use of Graph Theory to Support Map Generalization

Mackaness, William; Beard, Kate

doi:10.1559/152304093782637479

Cited by 95 publications

(31 citation statements)

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“…Previous work on the selection of important roads has focused on inferring semantic importance indirectly from the topology and geometry of the roads [Mackaness and Beard 1993;Thomson and Richardson 1995;Thomson and Richardson 1999;Jiang and Claramunt 2004]. In contrast, our system directly accesses this semantic information from the input data or the web.…”

Section: Semantic Featuresmentioning

confidence: 99%

Automatic generation of tourist maps

Grabler¹,

Agrawala²,

Sumner³

et al. 2008

ACM SIGGRAPH 2008 Papers

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Figure 1: (left) A digital map of San Francisco from Microsoft Live (www.live.com) AbstractTourist maps are essential resources for visitors to an unfamiliar city because they visually highlight landmarks and other points of interest. Yet, hand-designed maps are static representations that cannot adapt to the needs and tastes of the individual tourist. In this paper we present an automated system for designing tourist maps that selects and highlights the information that is most important to tourists. Our system determines the salience of map elements using bottom-up vision-based image analysis and top-down webbased information extraction techniques. It then generates a map that emphasizes the most important elements, using a combination of multiperspective rendering to increase visibility of streets and landmarks, and cartographic generalization techniques such as simplification, deformation, and displacement to emphasize landmarks and de-emphasize less important buildings. We show a number of automatically generated tourist maps of San Francisco and compare them to existing automated and manual approaches.

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Section: Semantic Featuresmentioning

confidence: 99%

Automatic generation of tourist maps

Grabler¹,

Agrawala²,

Sumner³

et al. 2008

ACM SIGGRAPH 2008 Papers

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“…The graph-based methods treat road networks as connected graphs and use pattern detection algorithms (Yang, Luan, and Li 2011) or concepts such as shortest/best path or minimum-spanning-trees, which serve as the basis for the selection (Mackaness and Beard 1993;Mackaness 1995). A special group of algorithms uses the dual graph approach at the topological level, where nodes represent roads and edges represent intersections of roads, respectively (Porta, Crucitti, and Latora 2006).…”

Section: Related Workmentioning

confidence: 99%

Road network selection for medium scales using an extended stroke-mesh combination algorithm

Benz

Weibel

2014

Cartography and Geographic Information Science

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The road network is an essential feature class in topographic maps and databases. Road network selection for smaller scales 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 paper was to develop an algorithm for automated road network selection from a large-scale (1:10,000) to a medium-scale database (1:50,000). The project was pursued in collaboration with swisstopo, the national mapping agency of Switzerland. Three algorithms (a stroke-based, a mesh-based, and a combined stroke-mesh algorithm) were implemented from the literature and analyzed using swisstopo's large-scale TLM3D spatial database, with requirements set forth by expert cartographers. Initial experiments showed that the combination algorithm performed best, yet still it could not meet all requirements. Therefore, extensions to the basic stroke-mesh algorithm were developed, significantly improving the selection result with real-world, large test databases. Three extensions introduce modifications to the stroke-mesh combination algorithm. Furthermore, two extensions include external feature classes, ensuring accessibility of points of interest and appropriate network density representation in settlement areas, respectively. The results were evaluated by expert cartographers, who concluded that the proposed approach is ready to be deployed in production at swisstopo.Abstract. The road network is an essential feature class in topographic maps and databases. Road network selection for smaller scales forms a perquisite 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 paper was to develop an algorithm for automated road network selection from a largescale (1:10,000) to a medium-scale database (1:50,000). The project was pursued in collaboration with swisstopo, the national mapping agency of Switzerland. Three algorithms (a stroke-based, a meshbased, and a combined stroke-mesh algorithm) were implemented from the literature and analyzed using swisstopo's large-scale TLM3D spatial database, with requirements set forth by expert cartographers. Initial experiments showed that the combination algorithm performed best, yet still it could not meet all requirements. Therefore, extensions to the basic stroke-mesh algorithm were developed, significantly improving the selection result with real-world, large test databases. Three extensions introduce modifications to the stroke-mesh combination algorithm. Furthermore, two extensions include external feature classes, ensuring accessibility of points of interest and appropriate network density representation in settlement areas, respectively. The results were evaluated by expert cartographers, who concluded that the proposed approach is ready to be deployed in production at swisstopo.

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“…Roads or railway networks form graphs as well. Such transport graphs can be used to generalise a road network connecting a set of cities by selecting roads in variants of the minimum spanning tree (Mackaness and Beard, 1993;Thomson and Richardson, 1995). Hence the connectivity of the transport network is assured.…”

Section: Minimum Spanning Trees (Mst)mentioning

confidence: 99%

Web service approaches for providing enriched data structures to generalisation operators

Neun

Burghardt

Weibel

2008

International Journal of Geographical Information Science

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Web service approaches for providing enriched data structures to generalisation operators Abstract Web service technologies can be used to establish an interoperable framework between different generalisation systems. In a previous article three categories of generalisation web services were identified, including support services, operator services and processing services. This paper focuses on the category of support services. In a service-based generalisation system, the purpose of support services is to assist the generalisation process by providing auxiliary measures, procedures and data structures that allow the representation of structural cartographic knowledge. The structural knowledge of the spatial and semantic context and the modelling of structural and spatial relationships is critical for the understanding of the role of cartographic features and thus for automated generalisation. Support services should extract and model this knowledge from the raw data and make it available to other generalisation operators. On the one hand the structural knowledge can be expressed by enriching map features with additional geometries or attributes. On the other hand, there exist various hierarchical and nonhierarchical relationships between map features, many of which can be represented by graph data structures. After a brief introduction to the interoperable web service framework, this paper proposes a taxonomy of generalisation support services and discusses its elements. It is then shown how the complex output of such services can be represented for use with web services and stored in a reusable fashion. Finally, the utilisation of support services is illustrated on four implementation examples of support services that also highlight the interactions with the generalisation operators that use these auxiliary services. Web service technologies can be used to establish an interoperable framework between different generalisation systems. In a previous article three categories of generalisation web services have been identified, including support services, operator services and processing services. This paper focuses on the category of support services. In a service-based generalisation system, the purpose of support services is to assist the generalisation process by providing auxiliary measures, procedures and data structures that allow to represent structural cartographic knowledge. The structural knowledge of the spatial and semantical context and the modelling of structural and spatial relationships is critical for the understanding of the role of cartographic features and thus for automated generalisation. Support services should extract and model this knowledge from the raw data and make it available to other generalisation operators. On the one hand the structural knowledge can be expressed by enriching map features with additional geometries or attributes. On the other hand there exist various hierarchical and non-hierarchical relationships between map features, many of which can be represented by graph da...

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Use of Graph Theory to Support Map Generalization

Cited by 95 publications

References 1 publication

Automatic generation of tourist maps

Automatic generation of tourist maps

Road network selection for medium scales using an extended stroke-mesh combination algorithm

Web service approaches for providing enriched data structures to generalisation operators

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