Urban topology and dynamics can assess the importance of green areas

Green areas are a crucial element in a city's evolution, improving citizens' lives, reducing the effects of climate change, and making possible the survival of other species in urban areas. Unfortunately, these effects are difficult to assess quantitatively for regulators, stakeholders, and experts, making the planning of city development. Here we present a method to estimate the impact of these areas on city life based on the network topology of the city itself and on a simple model of the dynamics of this structure. Movements between various areas of the city are simulated using an agent-based biased-diffusion process where citizens try to reach the nearest public green area (PGA) from their position, and the model is fed with real data about the density of populations in the cases of study. First, we define a centrality measure of city blocks based on average farness measured on the city network; this approach outperforms information based on the simple topology. We then improve this quantity by considering the occupation of PGAs, thereby providing a quantitative measure of PGA usage for regulators.

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Publication Details

Journal
Physical review. E
Published
2024-12-16
DOI
https://doi.org/10.1103/physreve.110.064128
Citations
1
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.28

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article

Urban topology and dynamics can assess the importance of green areas

Costanza Borghi, Saverio Francini, Bianca Galmarini, Paolo Costa et al.
1 citations
Physical review. E
Land Use and Ecosystem Services
0.28
article

Urban topology and dynamics can assess the importance of green areas

Costanza Borghi, Saverio Francini, Bianca Galmarini, Paolo Costa, Leonardo Chiesi, Guido Caldarelli, Gherardo Chirici, Jacopo Moi
article en
1 citations

Abstract

Green areas are a crucial element in a city's evolution, improving citizens' lives, reducing the effects of climate change, and making possible the survival of other species in urban areas. Unfortunately, these effects are difficult to assess quantitatively for regulators, stakeholders, and experts, making the planning of city development. Here we present a method to estimate the impact of these areas on city life based on the network topology of the city itself and on a simple model of the dynamics of this structure. Movements between various areas of the city are simulated using an agent-based biased-diffusion process where citizens try to reach the nearest public green area (PGA) from their position, and the model is fed with real data about the density of populations in the cases of study. First, we define a centrality measure of city blocks based on average farness measured on the city network; this approach outperforms information based on the simple topology. We then improve this quantity by considering the occupation of PGAs, thereby providing a quantitative measure of PGA usage for regulators.

Physical review. EVol. 110(6)
Royal Institution of Great Britain (GB), Ca' Foscari University of Venice (IT), Futuro (US), London Institute for Mathematical Sciences (GB), Institute for Complex Systems (IT), Ecolab (Germany) (DE), University of Florence (IT), University of Bologna (IT)
Ministero dell’Istruzione, dell’Università e della Ricerca
Sustainable cities and communities
Openalex Percentile: Top 39%
Land Use and Ecosystem Services
0.28
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