Simulating Future Urban Expansion in Monastir, Tunisia, as an Input for the Development of Future Risk Scenarios

Under scenarios of urbanization coupled with increasing frequency and intensity of natural hazards, urban disaster risk is set to rise. Simulating future urban expansion can provide relevant information for the development of future exposure scenarios and the identification of targeted risk reduction and adaptation strategies. Here, we present an urban growth simulation for the coastal city of Monastir, Tunisia. The approach integrates local knowledge and a data-driven urban growth model to simulate urban sprawl up to 2030. A business-as-usual projection is used to predict the future growth of the city based on the historical trend. Thirteen Landsat images for the period 1975 to 2017 were used to delineate past changes in urban land cover following the European Urban Atlas standard, which served as the main input for the urban growth model. The simulation revealed that the city’s residential area is likely to grow by 127 ha to an overall size of 1,690 ha by 2030, corresponding to an increase of 8.1% compared to the urban footprint of 2017. The outcomes of the analysis presented here served as an input for the spatial simulation of future exposure to flash floods in the case study area

Integrating Data-Driven and Participatory Modeling to Simulate Future Urban Growth Scenarios: Findings from Monastir, Tunisia

Current rapid urbanization trends in developing countries present considerable challenges to local governments, potentially hindering efforts towards sustainable urban development. To effectively anticipate the challenges posed by urbanization, participatory modeling techniques can help to stimulate future-oriented decision-making by exploring alternative development scenarios. With the example of the coastal city of Monastir, we present the results of an integrated urban growth analysis that combines the SLEUTH (slope, land use, exclusion, urban extent, transportation, and hill shade) cellular automata model with qualitative inputs from relevant local stakeholders to simulate urban growth until 2030. While historical time-series of Landsat data fed a business-as-usual prediction, the quantification of narrative storylines derived from participatory scenario workshops enabled the creation of four additional urban growth scenarios. Results show that the growth of the city will occur at different rates under all scenarios. Both the “business-as-usual” (BaU) prediction and the four scenarios revealed that urban expansion is expected to further encroach on agricultural land by 2030. The various scenarios suggest that Monastir will expand between 127–149 hectares. The information provided here goes beyond simply projecting past trends, giving decision-makers the necessary support for both understanding possible future urban expansion pathways and proactively managing the future growth of the city