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Title Integrating Data-Driven and Participatory Modeling to Simulate Future Urban Growth Scenarios: Findings from Monastir, Tunisia
ID_Doc 73098
Authors Harb, M; Garschagen, M; Cotti, D; Krätzschmar, E; Baccouche, H; Ben Khaled, K; Bellert, F; Chebil, B; Ben Fredj, A; Ayed, S; Shekhar, H; Hagenlocher, M
Title Integrating Data-Driven and Participatory Modeling to Simulate Future Urban Growth Scenarios: Findings from Monastir, Tunisia
Year 2020
Published Urban Science, 4, 1
DOI 10.3390/urbansci4010010
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.
Author Keywords participatory modeling; future urban expansion; SLEUTH; Business as Usual prediction; alternative scenarios
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Emerging Sources Citation Index (ESCI)
EID WOS:000620927300009
WoS Category Environmental Sciences; Environmental Studies; Geography; Regional & Urban Planning; Urban Studies
Research Area Environmental Sciences & Ecology; Geography; Public Administration; Urban Studies
PDF https://www.mdpi.com/2413-8851/4/1/10/pdf?version=1585294355
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