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Urban climate change adaptation: Exploring the implications of future land cover scenarios

Abstract Different land cover futures will have contrasting implications for cities working to adapt to the changing climate. This paper explores this issue, reporting on the application of a scenario-based land use modelling case study focused on Greater Manchester in North West England. It highlights that the interplay between varied drivers of change has the potential to generate contrasting land cover futures for the city-region, which will in turn influence climate change adaptation prospects. The case study pays specific attention to green infrastructure cover, as this can enhance the capacity of urban areas to adapt to climate change by providing functions such as evaporative cooling and rainwater infiltration. The two scenarios analysed within this paper connect, broadly, to the contrasting processes of expansion and shrinkage that are shaping cities worldwide. Where cities are expanding, stimulated by economic growth and increase in population, the danger is that associated land use change will pressure existing green infrastructure resources with a detrimental impact on adaptive capacity. Cities that are shrinking, or experiencing relative decline in comparison to other cities, face a different set of issues. Here, the emergence of vacant land provides an opportunity to secure adaptive capacity benefits associated with green infrastructure. With the processes of expansion and shrinkage projected to continue to influence the global landscape of cities, this research highlights that strategies are needed to protect and enhance green infrastructure in both contexts in order to maintain and build adaptive capacity and moderate climate-related risks.
- University of Salford United Kingdom
Adaptive capacity, Green infrastructure, Scenarios, Climate change, Urban, Land use change
Adaptive capacity, Green infrastructure, Scenarios, Climate change, Urban, Land use change
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).67 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
