A GIS-Cellular Automata-Based Model for Coupling Urban Sprawl and Flood Susceptibility Assessment

Scenario-Based Predictions of Urban Dynamics in Île-de-France Region: A New Combinatory Methodologic Approach of Variance Analysis and Frequency Ratio

Modelling land use dynamics is a critical scientific issue. Despite a diversity of models coming from the fields of remote sensing, geography, and economics, including multicriteria decision analysis and machine-learning models, taking into account the external driving factors of urbanization is still a main challenge. This study aims at simulating various land use development scenarios with global and local parameters. Thus, the developed approach is able to estimate and simulate the dynamic evolution of land use classes, the evolution of urban attractivity, both of which depend on several driving factors. The proposed scenarios incorporate anticipated global changes, such as an increase in oil prices and a decrease in wealth, and local spatial changes such as the provision of new rail lines and the development of new activity zones. The results of simulations, for the study area covering a great part of the Île-de-France region, show for the year 2050 an 18% increase in urban areas and a 25% decrease in bare soils, compared to the year 2018. Moreover, the increase of global prices and the reduction of income levels would increase the attractivity of public transport modes and drive urbanization around stations, reduce the accessible distances to public transport systems by 8.5%, reduce the dependency on private vehicles, and increase the concentrated saturation of urban development. These scenarios will serve as a basis for the deployment of nature-based solutions and renewable energy production.