Skeleton Line Extraction Method in Areas with Dense Junctions Considering Stroke Features

Li, Chengming; Yin, Yong; Wu, Pengda; Wu, Wei

doi:10.3390/ijgi8070303

Cited by 8 publications

(6 citation statements)

References 13 publications

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“…Detailed solutions for generating elongated polygons based on points denoting an elongated polygon line have been proposed in the literature [40][41][42]. TIN edges that do not intersect the main direction of the anticipated polygon in a perpendicular direction pose a problem in the presented solutions.…”

Section: Methods Of Generating the Axes Of Elongated Polygonsmentioning

confidence: 99%

“…A solution for extracting the skeleton line based on stroke features was described by [42]. In traditional approaches, the main structure and extension characteristics are difficult to maintain when dealing with dense junction areas due to the irregularity and complexity of junctions.…”

Section: Methods Of Generating the Axes Of Elongated Polygonsmentioning

confidence: 99%

“…They are also applied in specialist hydrographic research [43] and network analyses. Such solutions will also The described algorithms [37,[40][41][42] for determining the main polygon axes and river axes are highly complex. New and simple solutions for automating the generation of the main river axes based on raster and vector data are thus needed.…”

Section: Methods Of Generating the Axes Of Elongated Polygonsmentioning

confidence: 99%

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A Method for Generating the Centerline of an Elongated Polygon on the Example of a Watercourse

Lewandowicz

Flisek

2020

IJGI

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The centerlines of polygons can be generated with the use of various methods. The aim of this study was to propose an algorithm for generating the centerline of an elongated polygon based on the transformation of vector data. The proposed method involves the determination of base points denoting the direction of river flow. These points were also used to map two polygon boundaries. A Triangulated Irregular Network (TIN) was created based on the polygon’s breakpoints. Edges that intersect the river channel in a direction perpendicular to river flow (across) were selected from a set of TIN edges. The polygon was partitioned into segments with the use of the selected TIN edges. The midpoints of selected TIN edges were used to generate the polygon’s centerline based on topological relations. The presented methodology was tested on a polygon representing a 15-km-long section of a river intersecting the city of Olsztyn (a university center). The analyzed river is a highly meandering watercourse, and its channel is narrowed down by hydraulic structures. The river features an island and distributary channels. The generated centerline effectively fits the polygon, and, unlike the solution modeled with the Medial Axis Transformation (MAT) algorithm, it does not feature branching streams.

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Section: Methods Of Generating the Axes Of Elongated Polygonsmentioning

confidence: 99%

Section: Methods Of Generating the Axes Of Elongated Polygonsmentioning

confidence: 99%

Section: Methods Of Generating the Axes Of Elongated Polygonsmentioning

confidence: 99%

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A Method for Generating the Centerline of an Elongated Polygon on the Example of a Watercourse

Lewandowicz

Flisek

2020

IJGI

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“…In this study, strokes are built upon the arc-node topology structure of the road network considering the names and directions of the road segments at a junction. This process was described in detail in our previous study [ 25 ].…”

Section: Methodsmentioning

confidence: 99%

An elimination method for isolated meshes in a road network considering stroke edge feature

Wu³

et al. 2020

PLoS ONE

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The road network is the skeletal element of topographic maps at different scales. In general, urban roads are connected by road segments, thus forming a series of road meshes. Mesh elimination is a key step in evaluating the importance of roads during the road network data management and a prerequisite to the implementation of continuous multiscale spatial representation of road networks. The existing mesh-based method is an advanced road elimination method whereby meshes with the largest density are sequentially selected and road segments with the least importance in each mesh are eliminated. However, the road connectivity and integrity may be destroyed in specific areas by this method because some eliminated road segments could be located in the middle of road strokes. Therefore, this paper proposed an elimination method for isolated meshes in a road network considering stroke edge feature. First, small meshes were identified by using mesh density thresholds, which can be obtained by the sample data statistical algorithm. Thereafter, the small meshes related to the edge segments of road strokes were taken out and defined as stroke edge meshes, and the remaining small meshes were defined as stroke non-edge meshes. Second, by computing the mesh density of all stroke edge meshes, the mesh with the largest density was selected as the starting mesh, and the least important edge segment in the mesh was eliminated. The difference between the existing mesh-based method and the proposed method is that the starting mesh is a stroke edge mesh, not any given small mesh, and the eliminated segment is just only one of edge segments of strokes not chosen from among all segments. Third, mesh elimination was implemented by iteratively processing the stroke edge meshes with the largest mesh density until all of them were eliminated and their mesh density exceeded the threshold. The stroke non-edge meshes were directly preserved. Finally, a 1:10,000 topographic road map of an area in Jiangsu Province of China was used for validation. The experimental results show that for all stroke non-edge meshes and 23% of the stroke edge meshes, compared to the mesh-based method, the road stroke connectivity and integrity of road strokes were better preserved by the proposed method, and the remaining 77% of the elimination results for the stroke edge meshes were the same under the two methods.

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“…Step 2: To detect the adjacent line segment pairs and their bridge regions, a boundary constrained Delaunay triangulation (BCDT) is constructed [19,20,21] between the inner and outer rings. Specifically, more vertices are first added to the inner and outer rings at a certain interval to improve the robustness of the triangulation network.…”

Section: General Cleaning Algorithm For Different Visual Self-intersection Patternsmentioning

confidence: 99%

Investigation on Classification and Cleaning for Visually Self-Intersected Multipart Polygon With One Outer Ring

Guo

et al. 2020

IEEE Access

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In the field of cartography and geographic information systems, eliminating self-intersection problems is a key step in improving the reliability and robustness of spatial data representations, especially for the multipart polygon with one outer ring (MPOOR). In traditional studies, self-intersected MPOORs were identified by the topological intersection relationships between the line segments, but during map generalization or map spatial calculations, identifying only topological self-intersections is insufficient. Elements (vertices and line segments) that are topologically separated but have a distance smaller than the minimum visible distance (MVD) on the map also need to be considered to avoid graphic conflicts. The former condition is known as a topological self-intersection (TS), while the latter is known as a cartographic self-intersection (CS). Both the above two cases are called visual self-intersections in this paper, and a method for the classification and cleaning of visually self-intersected MPOORs is proposed. First, four visual selfintersection patterns are distinguished and defined, namely, intersecting, separating, collinear and combined, which are further divided into ten refined patterns that can be identified automatically based on the topological and distance relationships between the vertices and line elements. Second, general displacement and shrinkage algorithms are proposed to clean visually self-intersected MPOORs by taking the conflict regions and the MVD as constraints. Finally, real data from the Second National Land Survey of five counties in Guizhou Province in China are used for validation. The experimental results show that all the TS patterns identified by the Martinez-Llario method were successfully captured by the proposed method, and two TS patterns and four CS patterns were newly identified. Moreover, the proposed method yields more reasonable cleaning results that are not only topologically correct but also morphologically consistent and visually distinguishable.INDEX TERMS cartography and geographic information system, multipart polygon with one outer ring; visual self-intersection; refined classification; visual self-intersection cleaning This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.

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Skeleton Line Extraction Method in Areas with Dense Junctions Considering Stroke Features

Cited by 8 publications

References 13 publications

A Method for Generating the Centerline of an Elongated Polygon on the Example of a Watercourse

A Method for Generating the Centerline of an Elongated Polygon on the Example of a Watercourse

An elimination method for isolated meshes in a road network considering stroke edge feature

Investigation on Classification and Cleaning for Visually Self-Intersected Multipart Polygon With One Outer Ring

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