@misc{d0c43877afee4589bac293c472526651,
title = "Automatic Green Land-Use Generator for Urban Areas",
abstract = "Away to improve air quality (AQ) in urban areas consists of including more green infrastructures. To evaluate their effects, air quality simulations are employed to examine the behavior of pollutants and their dispersion patterns influenced by meteorological conditions. To study either the advantages or the drawbacks of modifying the green morphology of a city, the first step is to create a set of hypothetical green land-use maps that will later be used as input for air quality simulations. In this paper, we present an automatic green land-use generator, which uses the Monte Carlo method and Moore Neighborhood to create coherent land-use maps. These maps will be later on used to run simulations that show the impact on AQ of adding more green space to our cities.",
keywords = "Air Quality, Land-Use, Monte Carlo, Moore Neighborhood, Air Quality, Land-Use, Monte Carlo, Moore Neighborhood",
author = "Veronica Vidal and Carlos Carrillo and Ana Cort{\'e}s and Alba Badia and Gara Villalba",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.",
year = "2023",
month = oct,
day = "9",
doi = "10.1109/e-science58273.2023.10254800",
language = "English",
isbn = "9798350322231",
series = "Proceedings 2023 IEEE 19th International Conference on e-Science, e-Science 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",
type = "Other",
}
