Swarming landscapes, new pathways for resilient cities

Spatial planning and climate change science are part of a complex and uncertain context. The general response to this, and this can be seen throughout both the spatial planning and the climate change community, is to try to reduce uncertainty by introducing more procedures, developing more detailed models and increasing control of processes. However, gaining more detailed knowledge does not always increase certainty, or as Kevin Trenberth (2010) puts it: ‘More knowledge less certainty’. Both spatial planning and climate change, even more so if the two are linked, could gain from introducing self-organising principles. In order to be able to do so, the spatial system needs to be understood as a complex adaptive system, in which processes of self-organisation and emergence create ever changing spatial patterns, which, when used purposefully, will increase the system’s capability to respond effectively to unexpected change and uncertainty, for instance as a result of climate change. Providing the individual spatial elements in the landscape with a surplus of ‘technical skills’ will enable these spatial entities to self-organise and adapt more easily, thereby collaboratively increasing the adaptive capacity of the system. In order to create the conditions, which allow these self-organising processes to take place, current spatial planning practice needs to let go of its preference to regard spatial systems as being simple and problems as being tame. Complex Adaptive problems, such as climate change, cannot be dealt with within the current spatial planning framework. They require fundamental rethinking of the models underpinning spatial planning and introducing a new planning methodology. Swarm Planning claims to offer this methodology, using the dynamics of swarms as a metaphor. The behavioural patterns of swarms in nature are governed by the principles of self-organisation and emergence, rather than being planne