Automatic identification and feature recognition of the metro-led underground space in China based on point of interest data

Metro-led underground space (MUS) plays a crucial role in modern underground space utilisation. Recent studies have shown its great potential for high-quality urban development. However, limited evidence about MUS was available on a national scale, resulting in incomplete and unsystematic knowledge...

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Main Authors: Yun-Hao Dong, Fang-Le Peng, Yang Du, Yan-Qing Men
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2023-04-01
Series:Underground Space
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2467967422001064
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author Yun-Hao Dong
Fang-Le Peng
Yang Du
Yan-Qing Men
author_facet Yun-Hao Dong
Fang-Le Peng
Yang Du
Yan-Qing Men
author_sort Yun-Hao Dong
collection DOAJ
description Metro-led underground space (MUS) plays a crucial role in modern underground space utilisation. Recent studies have shown its great potential for high-quality urban development. However, limited evidence about MUS was available on a national scale, resulting in incomplete and unsystematic knowledge of MUS utilisation. The interaction relationship between MUS and the surrounding built environment also remains unclear. To fill the research gap, an automatic method for MUS identification and development features extraction was proposed based on point of interest data. We applied the method to identify the MUS in 28 Chinese cities and estimated the development status of MUS in China for the first time. The nationwide statistics of MUS and correlation analysis of development features were conducted. Results show that complex MUS (CMUS) share is significantly lower than that of simple MUS. Besides, CMUS development in China is primarily dominated by public transport and does not have a solid functional link to its surroundings. The comparative analysis of MUS development in four primary urban agglomerations was also conducted, and their development characteristics were discussed. The study aims to expand the planning toolkit and construct the MUS database, which sheds light on the data-driven planning for MUS.
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spelling doaj.art-67136ecb35ef447b872e44e79e59be5f2023-09-03T09:38:25ZengKeAi Communications Co., Ltd.Underground Space2467-96742023-04-019186199Automatic identification and feature recognition of the metro-led underground space in China based on point of interest dataYun-Hao Dong0Fang-Le Peng1Yang Du2Yan-Qing Men3Research Center for Underground Space and Department of Geotechnical Engineering, Tongji University, Shanghai 200092, ChinaResearch Center for Underground Space and Department of Geotechnical Engineering, Tongji University, Shanghai 200092, China; Corresponding author.Research Center for Underground Space and Department of Geotechnical Engineering, Tongji University, Shanghai 200092, ChinaJinan Rail Transit Group Co., LTD., Jinan, Shandong 250101, ChinaMetro-led underground space (MUS) plays a crucial role in modern underground space utilisation. Recent studies have shown its great potential for high-quality urban development. However, limited evidence about MUS was available on a national scale, resulting in incomplete and unsystematic knowledge of MUS utilisation. The interaction relationship between MUS and the surrounding built environment also remains unclear. To fill the research gap, an automatic method for MUS identification and development features extraction was proposed based on point of interest data. We applied the method to identify the MUS in 28 Chinese cities and estimated the development status of MUS in China for the first time. The nationwide statistics of MUS and correlation analysis of development features were conducted. Results show that complex MUS (CMUS) share is significantly lower than that of simple MUS. Besides, CMUS development in China is primarily dominated by public transport and does not have a solid functional link to its surroundings. The comparative analysis of MUS development in four primary urban agglomerations was also conducted, and their development characteristics were discussed. The study aims to expand the planning toolkit and construct the MUS database, which sheds light on the data-driven planning for MUS.http://www.sciencedirect.com/science/article/pii/S2467967422001064Development featuresMetro-led underground spacePoint of interest
spellingShingle Yun-Hao Dong
Fang-Le Peng
Yang Du
Yan-Qing Men
Automatic identification and feature recognition of the metro-led underground space in China based on point of interest data
Underground Space
Development features
Metro-led underground space
Point of interest
title Automatic identification and feature recognition of the metro-led underground space in China based on point of interest data
title_full Automatic identification and feature recognition of the metro-led underground space in China based on point of interest data
title_fullStr Automatic identification and feature recognition of the metro-led underground space in China based on point of interest data
title_full_unstemmed Automatic identification and feature recognition of the metro-led underground space in China based on point of interest data
title_short Automatic identification and feature recognition of the metro-led underground space in China based on point of interest data
title_sort automatic identification and feature recognition of the metro led underground space in china based on point of interest data
topic Development features
Metro-led underground space
Point of interest
url http://www.sciencedirect.com/science/article/pii/S2467967422001064
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AT yangdu automaticidentificationandfeaturerecognitionofthemetroledundergroundspaceinchinabasedonpointofinterestdata
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