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Population-Based Simulation of Urban Growth: The Italian Case Study

Authors: Claudia Cosentino; Federico Amato; Beniamino Murgante;

Population-Based Simulation of Urban Growth: The Italian Case Study

Abstract

Land take is one of the most studied phenomena in land use science. The increased attention to the issue of urban growth from both scientists and decision makers is justified by the dramatic negative effects on land use caused by anthropogenic activities. Within this context, researchers have developed and explored several models to forecast land use changes, some of which establish excellent scenario-based predictions of urban growth. However, there is still a lack of operative and user-friendly tools to be integrated into standard urban planning procedures. This paper explores the features of the recently published model FUTure Urban-Regional Environment Simulation integrated into the GRASSGIS environment, which generates urban growth simulation based on a plethora of driving variables. Specifically, the model was applied to the case study of urbanization in the Italian national territory. Hence, the aim of this work is to analyze the importance of population dynamics within the process of urban growth. A simulation of urban growth up to the year 2035 was performed. Results show that, despite the importance given to demographic aspects when defining urban policies over the last several decades, additional factors need to be considered during planning processes to overcome the housing issues currently experienced in Italy.

Country
Italy
Keywords

Cellular automata, Environmental effects of industries and plants, cellular automata, TJ807-830, 710, Urban growth, sustainability, TD194-195, Renewable energy sources, Environmental sciences, land use land cover changes, urban growth, Sustainability, Land use land cover change, GE1-350, GrassGIS

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    17
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Average
Top 10%
gold