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.