Graph convolutional networks for street network analysis with a case study of urban polycentricity in Chinese cities

IF 4.3 1区地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

International Journal of Geographical Information Science Pub Date : 2024-02-29 DOI:10.1080/13658816.2024.2321229

Ding Ma, Fangning He, Yang Yue, Renzhong Guo, Tianhong Zhao, Mingshu Wang

引用次数: 0

Abstract

Graph theory effectively explains urban structures via street–street connectivity. However, systematic comparisons of street structures across cities remain challenging. This study employs graph co...

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用于街道网络分析的图卷积网络与中国城市多中心案例研究

图论通过街道与街道之间的连通性有效地解释了城市结构。然而，对不同城市的街道结构进行系统比较仍具有挑战性。本研究利用图论来解释城市结构。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Geographical Information Science 地学-计算机：信息系统

CiteScore

11.00

自引率

7.00%

发文量

审稿时长

9 months

期刊介绍： International Journal of Geographical Information Science provides a forum for the exchange of original ideas, approaches, methods and experiences in the rapidly growing field of geographical information science (GIScience). It is intended to interest those who research fundamental and computational issues of geographic information, as well as issues related to the design, implementation and use of geographical information for monitoring, prediction and decision making. Published research covers innovations in GIScience and novel applications of GIScience in natural resources, social systems and the built environment, as well as relevant developments in computer science, cartography, surveying, geography and engineering in both developed and developing countries.