Urban topology and dynamics can assess green areas importance

TL;DR

This paper introduces a network topology-based method to quantitatively assess the importance of green areas in cities by modeling citizen movements and usage patterns, aiding urban planning and environmental strategies.

Contribution

The study presents a novel approach combining city network topology and agent-based dynamics to evaluate green areas' impact and usage in urban environments.

Findings

Centrality measure based on average farness outperforms simple topology.

Incorporating population occupation improves green area usage assessment.

Method provides quantitative insights for urban planning and regulation.

Abstract

Green areas are a crucial element in evolution of a city, contributing to improve citizens' life, to reduce effects of climate change, and to make possible the survival of other species in urban areas. Unfortunately, the above effects are difficult to assess quantitatively for regulators, stakeholders and experts, making troublesome the planning of city development. Here we present a method to estimate the impact of these areas in the city life based on the network topology of the city itself and on a simple model of dynamics on this structure. Movements between various areas of the city are simulated by means of 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. Firstly, we define a centrality measure of PGA's based on average farness measured on the city network; this approach outperforms information based on the simple topology. We then improve this quantity by taking into account the occupation of PGA's, thereby providing a quantitative measure of PGA usage for regulators.