On Farmland and Floodplains—Modeling Urban Growth Impacts Based on Global Population Scenarios in Pune, India
On Farmland and Floodplains—Modeling Urban Growth Impacts Based on Global Population Scenarios in Pune, India
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DOI：
10.3390/land12051051
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发表时间：
2023-05
期刊：
影响因子：
3.9
通讯作者：
Raphael Karutz;C. Klassert;S. Kabisch
中科院分区：
文献类型：
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作者：
Raphael Karutz;C. Klassert;S. Kabisch
全球南部的新兴特大城市面临着前所未有的变革动力，表现为人口、经济和物质的快速增长。预测相关的可持续性和复原力挑战需要了解未来的发展轨迹。全球变化模型提供了一致的高水平城市化情景。城市规模的城市增长模型准确地模拟了复杂的物理增长。然而，将全球尺度和地方尺度联系起来的建模方法还不够发达。这项工作介绍了一种新的方法，通过全球共享的社会经济路径为本地城市增长模型提供信息，通过元胞自动机和距离映射生成未来城市扩展和人口密度的一致地图。我们在印度浦那的案例中演示了这种方法。2050年前将探讨三种情况：一切照旧(BAU)、高城市化和低城市化。经过校准和验证，BAU情景产生了浦那55%的人口增长和90%的建设范围，带来了重大影响：浦那的核心城市进一步致密，高达60,000人/平方公里，给其紧张的基础设施增加了压力。此外，还有66%-70%的居民面临洪水风险。一半的城市扩张取代了农业，转化了167平方公里的土地。高度城市化的情景加剧了这些影响。这些结果表明，空间上明确的情景预测如何帮助确定城市化的影响并为长期规划提供信息。
Emerging megacities in the global south face unprecedented transformation dynamics, manifested in rapid demographic, economic, and physical growth. Anticipating the associated sustainability and resilience challenges requires an understanding of future trajectories. Global change models provide consistent high-level urbanization scenarios. City-scale urban growth models accurately simulate complex physical growth. Modeling approaches linking the global and the local scale, however, are underdeveloped. This work introduces a novel approach to inform a local urban growth model by global Shared Socioeconomic Pathways to produce consistent maps of future urban expansion and population density via cellular automaton and dasymetric mapping. We demonstrate the approach for the case of Pune, India. Three scenarios are explored until 2050: business as usual (BAU), high, and low urbanization. After calibration and validation, the BAU scenario yields a 55% growth in Pune’s population and 90% in built-up extent, entailing significant impacts: Pune’s core city densifies further with up to 60,000 persons/km2, adding pressure to its strained infrastructure. In addition, 66–70% more residents are exposed to flood risk. Half of the urban expansion replaces agriculture, converting 167 km2 of land. The high-urbanization scenario intensifies these impacts. These results illustrate how spatially explicit scenario projections help identify impacts of urbanization and inform long-term planning.