dorsal/arxiv
View SchemaStreet centrality vs. commerce and service locations in cities: a Kernel Density Correlation case study in Bologna, Italy
| Authors | Emanuele Strano, Alessio Cardillo, Valentino Iacoviello, Vito Latora, Roberto Messora, Sergio Porta, Salvatore Scellato |
|---|---|
| Categories | |
| ArXiv ID | physics/0701111 |
| URL | https://arxiv.org/abs/physics/0701111 |
Abstract
In previous research we defined a methodology for mapping centrality in urban networks. Such methodology, named Multiple Centrality Assessment (MCA), makes it possible to ascertain how each street is structurally central in a city according to several different notions of centrality, as well as different scales of "being central". In this study we investigate the case of Bologna, northern Italy, about how much higher street centrality statistically "determines" a higher presence of activities (shops and services). Our work develops a methodology, based on a kernel density evaluation, that enhances standard tools available in Geographic Information System (GIS) environment in order to support: 1) the study of how centrality and activities are distributed; 2) linear and non-linear statistical correlation analysis between centrality and activities, hereby named Kernel Density Correlation (KDC). Results offer evidence-based foundations that a strong correlation exists between centrality of streets, especially betweenness centrality, and the location of shops and services at the neighbourhood scale. This issue is at the heart of the current debate in urban planning and design towards the making of more sustainable urban communities for the future. Our results also support the "predictive" capability of the MCA model as a tool for sustainable urban design.
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"abstract": "In previous research we defined a methodology for mapping centrality in urban\nnetworks. Such methodology, named Multiple Centrality Assessment (MCA), makes\nit possible to ascertain how each street is structurally central in a city\naccording to several different notions of centrality, as well as different\nscales of \"being central\". In this study we investigate the case of Bologna,\nnorthern Italy, about how much higher street centrality statistically\n\"determines\" a higher presence of activities (shops and services). Our work\ndevelops a methodology, based on a kernel density evaluation, that enhances\nstandard tools available in Geographic Information System (GIS) environment in\norder to support: 1) the study of how centrality and activities are\ndistributed; 2) linear and non-linear statistical correlation analysis between\ncentrality and activities, hereby named Kernel Density Correlation (KDC).\nResults offer evidence-based foundations that a strong correlation exists\nbetween centrality of streets, especially betweenness centrality, and the\nlocation of shops and services at the neighbourhood scale. This issue is at the\nheart of the current debate in urban planning and design towards the making of\nmore sustainable urban communities for the future. Our results also support the\n\"predictive\" capability of the MCA model as a tool for sustainable urban\ndesign.",
"arxiv_id": "physics/0701111",
"authors": [
"Emanuele Strano",
"Alessio Cardillo",
"Valentino Iacoviello",
"Vito Latora",
"Roberto Messora",
"Sergio Porta",
"Salvatore Scellato"
],
"categories": [
"physics.soc-ph"
],
"title": "Street centrality vs. commerce and service locations in cities: a Kernel Density Correlation case study in Bologna, Italy",
"url": "https://arxiv.org/abs/physics/0701111"
},
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