Spatial network structure and driving factors of human settlements in three Northeastern provinces of China
IntroductionUrban human settlements' spatial network structures have emerged as crucial determinants impacting their health and sustainability. Understanding the influencing factors is pivotal for enhancing these settlements. This study focuses on 34 prefecture-level cities in Northeastern Chin...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-09-01
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| Series: | Frontiers in Ecology and Evolution |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fevo.2023.1206808/full |
| _version_ | 1827822400369065984 |
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| author | Rui Song Rui Song Rui Song Xueming Li Xueming Li Xueming Li Xinyu Hou Xinyu Hou Xinyu Hou |
| author_facet | Rui Song Rui Song Rui Song Xueming Li Xueming Li Xueming Li Xinyu Hou Xinyu Hou Xinyu Hou |
| author_sort | Rui Song |
| collection | DOAJ |
| description | IntroductionUrban human settlements' spatial network structures have emerged as crucial determinants impacting their health and sustainability. Understanding the influencing factors is pivotal for enhancing these settlements. This study focuses on 34 prefecture-level cities in Northeastern China from 2005 to 2020. It employs a modified gravitational model to establish spatial relationships among urban human settlements. Social network analysis techniques, including modularity and the quadratic assignment procedure (QAP) regression model, are introduced to analyze the network's characteristics and driving factors.MethodsA modified gravitational model is applied to create the spatial association network of urban human settlements. Social network analysis tools, along with modularity and the QAP regression model, are utilized to investigate the network's attributes and influencing elements. The study evaluates the evolution of spatial correlation, network cohesion, hierarchy, and efficiency.ResultsThroughout the study period, spatial correlation among urban human settlements in Northeastern China progressively intensified. However, the network exhibited relatively low density (0.217675), implying limited interconnectivity among cities. The average network hierarchy was 0.178225, indicating the need for optimization, while the average network efficiency was 0.714025, reflecting fewer redundant relationships. The analysis reveals the emergence of a polycentric network pattern with core and sub-core cities like Shenyang, Dalian, Changchun, Daqing, and Harbin. The urban network configuration has largely stabilized. The spatial association network showcases the intertwining of "small groups" and community organizations. Geographic proximity and merit-based linkages govern feature flow. Measures such as breaking administrative barriers, reducing flow time and distance, boosting resident income, and increasing government investment are identified to foster balanced network development and structural optimization.DiscussionThe research underscores the increasing spatial correlation and evolving network pattern among urban human settlements in Northeastern China. Despite the observed strengthening correlation, challenges related to network cohesion and hierarchy persist. The formation of a polycentric network signifies positive progress in urban development. The study highlights the importance of proximity and merit-based connections for feature flow. The proposed measures offer pathways to enhance network development and optimize structure, promoting holistic urban settlement growth and sustainability. |
| first_indexed | 2024-03-12T01:57:29Z |
| format | Article |
| id | doaj.art-b1cecb790e8e4bcca282329af516805e |
| institution | Directory Open Access Journal |
| issn | 2296-701X |
| language | English |
| last_indexed | 2024-03-12T01:57:29Z |
| publishDate | 2023-09-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Ecology and Evolution |
| spelling | doaj.art-b1cecb790e8e4bcca282329af516805e2023-09-07T22:10:12ZengFrontiers Media S.A.Frontiers in Ecology and Evolution2296-701X2023-09-011110.3389/fevo.2023.12068081206808Spatial network structure and driving factors of human settlements in three Northeastern provinces of ChinaRui Song0Rui Song1Rui Song2Xueming Li3Xueming Li4Xueming Li5Xinyu Hou6Xinyu Hou7Xinyu Hou8School of Geography, Liaoning Normal University, Dalian, ChinaCenter for Human Settlements, Liaoning Normal University, Dalian, ChinaResearch Base of Urban Agglomeration in Central-South Liaoning of China Urban Agglomeration Research Base Alliance, Dalian, ChinaSchool of Geography, Liaoning Normal University, Dalian, ChinaCenter for Human Settlements, Liaoning Normal University, Dalian, ChinaResearch Base of Urban Agglomeration in Central-South Liaoning of China Urban Agglomeration Research Base Alliance, Dalian, ChinaSchool of Geography, Liaoning Normal University, Dalian, ChinaCenter for Human Settlements, Liaoning Normal University, Dalian, ChinaResearch Base of Urban Agglomeration in Central-South Liaoning of China Urban Agglomeration Research Base Alliance, Dalian, ChinaIntroductionUrban human settlements' spatial network structures have emerged as crucial determinants impacting their health and sustainability. Understanding the influencing factors is pivotal for enhancing these settlements. This study focuses on 34 prefecture-level cities in Northeastern China from 2005 to 2020. It employs a modified gravitational model to establish spatial relationships among urban human settlements. Social network analysis techniques, including modularity and the quadratic assignment procedure (QAP) regression model, are introduced to analyze the network's characteristics and driving factors.MethodsA modified gravitational model is applied to create the spatial association network of urban human settlements. Social network analysis tools, along with modularity and the QAP regression model, are utilized to investigate the network's attributes and influencing elements. The study evaluates the evolution of spatial correlation, network cohesion, hierarchy, and efficiency.ResultsThroughout the study period, spatial correlation among urban human settlements in Northeastern China progressively intensified. However, the network exhibited relatively low density (0.217675), implying limited interconnectivity among cities. The average network hierarchy was 0.178225, indicating the need for optimization, while the average network efficiency was 0.714025, reflecting fewer redundant relationships. The analysis reveals the emergence of a polycentric network pattern with core and sub-core cities like Shenyang, Dalian, Changchun, Daqing, and Harbin. The urban network configuration has largely stabilized. The spatial association network showcases the intertwining of "small groups" and community organizations. Geographic proximity and merit-based linkages govern feature flow. Measures such as breaking administrative barriers, reducing flow time and distance, boosting resident income, and increasing government investment are identified to foster balanced network development and structural optimization.DiscussionThe research underscores the increasing spatial correlation and evolving network pattern among urban human settlements in Northeastern China. Despite the observed strengthening correlation, challenges related to network cohesion and hierarchy persist. The formation of a polycentric network signifies positive progress in urban development. The study highlights the importance of proximity and merit-based connections for feature flow. The proposed measures offer pathways to enhance network development and optimize structure, promoting holistic urban settlement growth and sustainability.https://www.frontiersin.org/articles/10.3389/fevo.2023.1206808/fullhuman settlementsspatially associative structureNortheastern Chinainfluencing factorsfeature flow |
| spellingShingle | Rui Song Rui Song Rui Song Xueming Li Xueming Li Xueming Li Xinyu Hou Xinyu Hou Xinyu Hou Spatial network structure and driving factors of human settlements in three Northeastern provinces of China Frontiers in Ecology and Evolution human settlements spatially associative structure Northeastern China influencing factors feature flow |
| title | Spatial network structure and driving factors of human settlements in three Northeastern provinces of China |
| title_full | Spatial network structure and driving factors of human settlements in three Northeastern provinces of China |
| title_fullStr | Spatial network structure and driving factors of human settlements in three Northeastern provinces of China |
| title_full_unstemmed | Spatial network structure and driving factors of human settlements in three Northeastern provinces of China |
| title_short | Spatial network structure and driving factors of human settlements in three Northeastern provinces of China |
| title_sort | spatial network structure and driving factors of human settlements in three northeastern provinces of china |
| topic | human settlements spatially associative structure Northeastern China influencing factors feature flow |
| url | https://www.frontiersin.org/articles/10.3389/fevo.2023.1206808/full |
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