Abstract

Incorporating low probability and high impact events in land use and transport planning (e.g., COVID-19 pandemic) remains as a challenge. Scenario-building techniques are frequently used to examine and incorporate those deep uncertainties into planning processes. However, limited attention has been paid to explore how scenario-building visions can contribute to design adaptation policy pathways, which further increases land use and transport resilience against unexpected and low probability events. This paper initially shows a theoretical framework that links scenario-building visions to adaptive planning, defining four potential adaptation policy pathways: linear, priority-oriented, outcomes-oriented, and winding. Such adaptation pathways are based on comparing both priority of planning goals and outcomes differences across a set of long-term visions and the basic policy pathway adopted. The theoretical approach is supported by an empirical analysis implemented in the Madrid Metropolitan Area (Spain), where a scenario-building process has been developed, creating three long-term visions that differ from the basic pathway: “Non-motorized city centers”, “Overpopulation”, and “High levels of insecurity in urban areas”. The comparison between long-term visions and the basic pathway was made by surveying a group of experts and stakeholders, distilling different adaptation pathways for the case study. The obtained results support the theoretical framework described, opening a discussion about its robustness, implementability, effectiveness, and limitations for real planning processes.

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