A spatially explicit backcasting approach for sustainable land-use planning

Abstract

General backcasting as a decision support and planning method starts from desired future states and simulates developments backwards until reaching the present state. Development pathways that reveal steps to be taken to reach a certain future state, and milestones that serve as interim goals, are created during the process. Backcasting has hitherto only been applied in workshops or as a theoretical framework and no spatially explicit backcasting model has previously been established. This paper presents the development of a spatially explicit backcasting model. The proposed model first creates a future scenario utilizing an agent-based model and then simulates backwards. It is implemented using the programming language Python. The model has been applied to a case study for sustainable land-use planning in Salzburg, Austria. The results of the model run show a successful backcasting of land-use classes from a future state back to the present, in 10 year time steps.

Keywords:

• backcasting
• land-use planning
• sustainability
• decision support

Acknowledgements

The authors want to thank Roland Hufnagl for his programming support and Ed Manning for his many valuable comments and for proof reading the article. Finally, thanks to the reviewers for their comments which improved the paper substantially.

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

The research was funded by the Austrian Science Fund (FWF) through the Doctoral College GIScience [DK W 1237-N23].