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

Harb, Mostapha, Garschagen, Matthias, Cotti, Davide, Kratzschmar, Elke, Baccouche, Hayet, Ben Khaled, Karem, Bellert, Felicitas, Chebil, Bouraoui, Ben Fredj, Anis, Ayed, Sonia, Shekhar, Himanshu and Hagenlocher, Michael, (2020). Integrating Data-Driven and Participatory Modeling to Simulate Future Urban Growth Scenarios: Findings from Monastir, Tunisia. Urban Science, 4(1), 1-13

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    Author Harb, Mostapha
    Garschagen, Matthias
    Cotti, Davide
    Kratzschmar, Elke
    Baccouche, Hayet
    Ben Khaled, Karem
    Bellert, Felicitas
    Chebil, Bouraoui
    Ben Fredj, Anis
    Ayed, Sonia
    Shekhar, Himanshu
    Hagenlocher, Michael
    Title Integrating Data-Driven and Participatory Modeling to Simulate Future Urban Growth Scenarios: Findings from Monastir, Tunisia
    Appearing in Urban Science
    Volume 4
    Issue No. 1
    Publication Date 2020-02-27
    Place of Publication Basel
    Publisher MDPI
    Start page 1
    End page 13
    Language eng
    Abstract 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.
    Keyword Participatory modeling
    Future urban expansion
    SLEUTH
    Business as usual prediction
    Alternative scenarios
    Copyright Holder MDPI
    Copyright Year 2020
    Copyright type Creative commons
    DOI 10.3390/urbansci4010010
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    Created: Fri, 28 Feb 2020, 22:00:11 JST by Aarti Basnyat on behalf of UNU EHS