Grid Pattern Recognition in Road Networks Using Link Graph

LI Hao; GUO Li; WANG Yunge; JIANG Jingli

doi:10.13203/j.whugis20190300

Volume 47 Issue 1

Jan. 2022

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Geomatics and Information Science of Wuhan University > 2022 > 47(1): 126-132. > DOI: 10.13203/j.whugis20190300

LI Hao, GUO Li, WANG Yunge, JIANG Jingli. Grid Pattern Recognition in Road Networks Using Link Graph[J]. Geomatics and Information Science of Wuhan University, 2022, 47(1): 126-132. DOI: 10.13203/j.whugis20190300

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Grid Pattern Recognition in Road Networks Using Link Graph

1.
Institute of Geographical Spatial Information, Information Engineering University, Zhengzhou 450001, China

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The National Natural Science Foundation of China 41471314

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Author Bio:
LI Hao, master, specializes in the road networks pattern recognition and road matching. E-mail: 1017920864@qq.com
Corresponding author:
GUO Li, PhD, associate professor. E-mail: gl_750312@163.com
Received Date: October 11, 2019
Published Date: January 04, 2022

Graphical Abstract

Abstract

Abstract

Objectives The road network is the skeleton of a city and the road pattern refers to the shape of roads that can be clearly named. Identifying road patterns helps to understand the structures of cities and find more potential knowledge. However, urban road networks are complicated, and it is very difficult to identify the road structure.
Methods A link-graph-based method is proposed for recognizing the grid pattern in road networks. This method uses the link graph to represent road networks, in which nodes represent road segments and links represent intersections. It converts recognizing the grid pattern in road networks into searching for loops in the link graph. Five parameters are defined to select nodes and links that would match the grid conditions in the graph. The breadth-first search algorithm is used to search the loop in the link graph.
Results By mapping links and nodes in the link graph back to road segments, we can identify the grid pattern in road networks. This method can still work in more complicated road networks.
Conclusions The result shows that the proposed method can effectively recognize the grid pattern in road networks. Other road patterns can be further identified through analysis of the characteristics of the road connection.
- link graph,
- grid pattern,
- breadth-first search,
- graph search,
- grid loops

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