Artikel ; Online: Exploring the Relationship between Land Use and Congestion Source in Xi’an
Sustainability, Vol 15, Iss 9328, p
A Multisource Data Analysis Approach
2023 Band 9328
Abstract: Traffic congestion is a critical problem in urban areas, and understanding the relationship between land use and congestion source is crucial for traffic management and urban planning. This study investigates the relationship between land-use ... ...
Abstract | Traffic congestion is a critical problem in urban areas, and understanding the relationship between land use and congestion source is crucial for traffic management and urban planning. This study investigates the relationship between land-use characteristics and congestion pattern features of source parcels in the Second Ring Road of Xi’an, China. The study combines cell-phone data, POI data, and land-use data for the empirical analysis, and uses a spatial clustering approach to identify congested road sections and trace them back to source parcels. The correlations between building factors and congestion patterns are explored using the XGBoost algorithm. The results reveal that residential land and residential population density have the strongest impact on congestion clusters, followed by lands used for science and education and the density of the working population. The study also shows that a small number of specific parcels are responsible for the majority of network congestion. These findings have important implications for urban planners and transportation managers in developing targeted strategies to alleviate traffic congestion during peak periods. |
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Schlagwörter | human mobility ; congestion source analysis ; land use ; cell-phone data ; machine learning ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350 |
Thema/Rubrik (Code) | 380 |
Sprache | Englisch |
Erscheinungsdatum | 2023-06-01T00:00:00Z |
Verlag | MDPI AG |
Dokumenttyp | Artikel ; Online |
Datenquelle | BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl) |
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