Generating hierarchical strokes from urban street networks based on spatial pattern recognition

Wang, Jinhu; Luan, Xuechen; Li, Qingquan

doi:10.1080/13658816.2011.570270

Cited by 50 publications

(46 citation statements)

References 15 publications

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“…In contrast to other clustering methods, such as K-Means, these methods do not require the number of clusters as an input. While Yang et al (2011) used network distance, we computed Euclidean distance due to the very short distances between nodes that should be generalized into a single intersection. In border cases, such as a narrow barrier that splits an intersection area, this could cause issues that require user intervention.…”

Section: Methodsmentioning

confidence: 99%

Tessellating Urban Space based on Street Intersections and Barriers to Movement

Gräser¹

2017

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This paper presents a novel method to partition urban space with respect to its mobility network rather than abstract administrative boundaries or simple grids. The main goal of our method is to support mobility infrastructure planning and optimization in an urban environment. To this end, our tessellation, which is based on constrained Voronoi tessellation, generates cells that are compact and centred around street intersections. Furthermore, it takes into account unsuitable areas and barriers that obstruct movement through urban space. The resulting cells are fine-grained planning units that reflect the characteristics of the underlying mobility network. Potential applications include demand modelling, location planning and optimization for bicycle-and car-sharing systems, or public transport stops.

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Section: Methodsmentioning

confidence: 99%

Tessellating Urban Space based on Street Intersections and Barriers to Movement

Gräser¹

2017

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“…On the other hand, if we assume the vertices are streets and two vertices are connected whenever the streets they represent intersect, we obtain a dual representation of the street network [20]. Constructing a dual-representation is closely related to the problem of detecting network strokes [42]. It was noted by Crucitti et al [37] that a dual representation corresponds to an abandonment of metric distance; a street is a single node irrespective of its length.…”

Section: Network Constructionmentioning

confidence: 99%

Characterising the metric and topological evolution of OpenStreetMap network representations

Corcoran

Mooney

2013

Eur. Phys. J. Spec. Top.

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Abstract. OpenStreetMap (OSM) is a collaborative project to create a free editable map database of the world. This paper presents an analysis of the evolution of OSM street network representations. Three urban areas in Ireland were analysed where each evolves from containing little street network detail to a highly detailed street network. In order to characterise this evolution a number of metric and topological characteristics were computed. Some characteristics exhibited broadly similar behaviour in each region. This may be a attributed to similarities in the degree of contributor activity and intrinsic universal mapping procedures exhibited by contributors.

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“…The aggregation of similarity measures is a difficult problem that can be further optimized within our approach, for example by using CRITIC criterion (see e.g. Yang et al 2011). …”

Section: The Integration Function Is Described As Followsmentioning

confidence: 99%

“…This hierarchies are able to be extracted through network analysis (Jiang and Claramunt 2002;Jiang and Harrie 2004;Tomko et al 2008;Porta et al 2006aPorta et al , 2006b). We use the approach proposed by Yang et al (2011) to calculate road stroke length, degree, closeness and betweenness centralities as parameters to select high hierarchical roads. Degree centrality is calculated as the number of strokes connected to a given stroke.…”

Section: Golbal Structure Extraction From Urban Road Networkmentioning

confidence: 99%

A Structure-Based Approach for Matching Road Junctions With Different Coordinate Systems

Luana

2012

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Effective matching algorithm of multi-source road networks is of vital importance for integration, updating and maintenance. In traditional matching methods, buffering and geometrical distances are basic strategies for potential matches searching, and the coordinate systems need to be similar. These methods may be invalid if the coordinate systems are unknown. Therefore, a novel approach of comparing the structures of urban road networks based on skeleton extraction is proposed in this paper. Firstly, the similarity measurement between junctions is described by a cluster comparison consisted with its neighbour junctions. And then the hierarchical strokes are recognized as a global structure to match, which eliminates the effect of the different coordinate systems. Finally, graphs converted from hierarchical skeletons of road network in different coordinate systems are compared and the most probable junction correspondences are established with maximum common subgraph algorithm. Based on the corresponding junctions, an affine transformation is able to be established between two unknown coordinate systems, and the remaining junctions matching will be conducted by traditional geometric methods. An experiment of matching road networks is carried out without any other geographic positional information. The result shows that no matter how significant the difference of coordinate systems are, it is still able to find the correct matches, which is impossible by traditional methods.Xuechen Luan (1985-): Ph.D candidate, majors in data matching, modeling and LoD representation in urban road networks.

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Generating hierarchical strokes from urban street networks based on spatial pattern recognition

Cited by 50 publications

References 15 publications

Tessellating Urban Space based on Street Intersections and Barriers to Movement

Tessellating Urban Space based on Street Intersections and Barriers to Movement

Characterising the metric and topological evolution of OpenStreetMap network representations

A Structure-Based Approach for Matching Road Junctions With Different Coordinate Systems

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