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

Q3 Social Sciences GI_Forum Pub Date : 2019-05-17 DOI:10.1553/GISCIENCE_2019_01_S3
Mustapha Harb, M. Hagenlocher, D. Cotti, E. Kratzschmar, Hayet Baccouche, K. B. Khaled, Felicitas Bellert, Bouraoui Chebil, Anis Ben Fredj, S. Ayed, M. Garschagen
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引用次数: 1

Abstract

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.
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模拟突尼斯Monastir未来城市扩张,为未来风险情景的发展提供输入
在城市化的情况下,加上自然灾害的频率和强度不断增加,城市灾害风险必将上升。模拟未来城市扩张可以为制定未来暴露情景和确定有针对性的风险降低和适应策略提供相关信息。在这里,我们提出了一个突尼斯沿海城市莫纳斯提尔的城市增长模拟。该方法将当地知识与数据驱动的城市增长模型相结合,模拟到2030年的城市扩张。商业常规预测是根据历史趋势预测城市未来的增长。根据欧洲城市地图集标准,使用1975年至2017年期间的13张Landsat图像来描绘城市土地覆盖的过去变化,这是城市增长模型的主要输入。模拟显示,到2030年,该市的住宅面积可能会增加127公顷,达到1690公顷,与2017年的城市足迹相比,增长了8.1%。本文提供的分析结果可作为案例研究区域未来遭受山洪暴发的空间模拟的输入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
GI_Forum
GI_Forum Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
1.10
自引率
0.00%
发文量
9
审稿时长
23 weeks
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