Spatial resilience for climate change: the swarm and the plan

This paper reports on conducted research on the edge of increasing climate adaptation through spatial planning, dealing with wicked problems in spatial planning and science-policy interaction. In the research the problem is defined as follows. In a turbulent timeframe, when many problems are wicked, current policymaking and the planning system in many countries are tame. It is estimated that an adjusted planning approach, making it suitable for wicked problems, enhances the spatial resilience of an area. The objectives of the research are to: Develop an innovative planning approach, in which wicked problems can be tackled; Underpin that the approach increases spatial resilience and is able to deal with unexpected changes; Gain insights on how spatial resilience and based on this, preparedness to adapt to the impacts of climate change, can be increased. In the research approach the main issue is to make use of wicked characteristics, concepts and knowledge that are well known in other scientific fields, such as complexity theory, complex adaptive systems theory, organisational complexity and network analyses. Build on the content of these research fields a new spatial planning approach is developed. This new approach tackles wicked problems and incorporates them into spatial plans. The methodology includes three basic steps: analysis of the networks, definition of focal points as starting points of development, connectedness and the zones of influence with unplanned area. Based on this first analytical step the future resources, such as energy water and food, are safeguarded. The final stage defines the occupation patterns that may evolve over time and are dependent on future changes. The results of the study are the following: 1. Definition of swarm planning principles; 2. Development of the swarm planning methodology; 3. Build a new, innovative planning theory; 4. Concrete results in the form of designs, scenarios, maps and strategies, which are derived from pilot projects in Dutch and Australian contexts, in which the swarm planning approach is developed and tested