Metropolitan spatial structure analysis based on the identification of commuting zones with Nanjing City as an example
Commuting zone research is critical to the understanding of the operational rules of the metropolitan spatial structure and improving spatial performance. This study aims to identify the main commuting centers and zones by using cellular data with Nanjing City as the example. This study analyzes the...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
KeAi Communications Co., Ltd.
2023-04-01
|
Series: | Frontiers of Architectural Research |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2095263522000954 |
_version_ | 1811155509149958144 |
---|---|
author | Yan He Xiao Wu Linjin Wang |
author_facet | Yan He Xiao Wu Linjin Wang |
author_sort | Yan He |
collection | DOAJ |
description | Commuting zone research is critical to the understanding of the operational rules of the metropolitan spatial structure and improving spatial performance. This study aims to identify the main commuting centers and zones by using cellular data with Nanjing City as the example. This study analyzes the operational features of the internal spatial structures of the city from two dimensions by merging multi-source data, namely, commuting centers and zones, thus achieving an understanding of the existing problems with the urban spatial structures and their internal causes. Results showed that the commuting zones of Nanjing are distributed in a pattern of “multiple commuting centers”, with Xinjiekou–Hunan Road and Hongwu Road–Chaotiangong–Shuangtang as the core, Mochou Lake as the main commuting area, and Dongshan and Jiangpu as the secondary commuting zones. Significant differences and similarities are discovered in our comparisons along the two dimensions of commuting zones and centers in terms of spatial structural factors, such as land use, transportation, and commuting in the city. The similarity is shown as a common declining trend in the values of all our indicators with the increase in the distance of commuting zones from the city center. However, the differences are significant in terms of the clustering features of the various parameters concerning commuting centers and zones. Specifically, four clustering patterns are discovered, namely, “monocentric clustering”, “circular monocentric clustering”, “polycentric clustering”, and “sparsely dotted distribution”. This study sheds light on the existing problems with the city's spatial structure and proposes some overall suggestions toward urban spatial structure improvement on the basis of these findings. |
first_indexed | 2024-04-10T04:35:30Z |
format | Article |
id | doaj.art-c206846646bd4344a5ff6d9c900ab88f |
institution | Directory Open Access Journal |
issn | 2095-2635 |
language | English |
last_indexed | 2024-04-10T04:35:30Z |
publishDate | 2023-04-01 |
publisher | KeAi Communications Co., Ltd. |
record_format | Article |
series | Frontiers of Architectural Research |
spelling | doaj.art-c206846646bd4344a5ff6d9c900ab88f2023-03-10T04:34:48ZengKeAi Communications Co., Ltd.Frontiers of Architectural Research2095-26352023-04-01122291307Metropolitan spatial structure analysis based on the identification of commuting zones with Nanjing City as an exampleYan He0Xiao Wu1Linjin Wang2School of Architecture, Southeast University, Nanjing, 210096, ChinaCorresponding author.; School of Architecture, Southeast University, Nanjing, 210096, ChinaSchool of Architecture, Southeast University, Nanjing, 210096, ChinaCommuting zone research is critical to the understanding of the operational rules of the metropolitan spatial structure and improving spatial performance. This study aims to identify the main commuting centers and zones by using cellular data with Nanjing City as the example. This study analyzes the operational features of the internal spatial structures of the city from two dimensions by merging multi-source data, namely, commuting centers and zones, thus achieving an understanding of the existing problems with the urban spatial structures and their internal causes. Results showed that the commuting zones of Nanjing are distributed in a pattern of “multiple commuting centers”, with Xinjiekou–Hunan Road and Hongwu Road–Chaotiangong–Shuangtang as the core, Mochou Lake as the main commuting area, and Dongshan and Jiangpu as the secondary commuting zones. Significant differences and similarities are discovered in our comparisons along the two dimensions of commuting zones and centers in terms of spatial structural factors, such as land use, transportation, and commuting in the city. The similarity is shown as a common declining trend in the values of all our indicators with the increase in the distance of commuting zones from the city center. However, the differences are significant in terms of the clustering features of the various parameters concerning commuting centers and zones. Specifically, four clustering patterns are discovered, namely, “monocentric clustering”, “circular monocentric clustering”, “polycentric clustering”, and “sparsely dotted distribution”. This study sheds light on the existing problems with the city's spatial structure and proposes some overall suggestions toward urban spatial structure improvement on the basis of these findings.http://www.sciencedirect.com/science/article/pii/S2095263522000954Commuting centerCommuting zoneUrban spaceCellular signal dataNanjing |
spellingShingle | Yan He Xiao Wu Linjin Wang Metropolitan spatial structure analysis based on the identification of commuting zones with Nanjing City as an example Frontiers of Architectural Research Commuting center Commuting zone Urban space Cellular signal data Nanjing |
title | Metropolitan spatial structure analysis based on the identification of commuting zones with Nanjing City as an example |
title_full | Metropolitan spatial structure analysis based on the identification of commuting zones with Nanjing City as an example |
title_fullStr | Metropolitan spatial structure analysis based on the identification of commuting zones with Nanjing City as an example |
title_full_unstemmed | Metropolitan spatial structure analysis based on the identification of commuting zones with Nanjing City as an example |
title_short | Metropolitan spatial structure analysis based on the identification of commuting zones with Nanjing City as an example |
title_sort | metropolitan spatial structure analysis based on the identification of commuting zones with nanjing city as an example |
topic | Commuting center Commuting zone Urban space Cellular signal data Nanjing |
url | http://www.sciencedirect.com/science/article/pii/S2095263522000954 |
work_keys_str_mv | AT yanhe metropolitanspatialstructureanalysisbasedontheidentificationofcommutingzoneswithnanjingcityasanexample AT xiaowu metropolitanspatialstructureanalysisbasedontheidentificationofcommutingzoneswithnanjingcityasanexample AT linjinwang metropolitanspatialstructureanalysisbasedontheidentificationofcommutingzoneswithnanjingcityasanexample |