A spatially explicit backcasting approach for sustainable land-use planning
Authored by Eva Haslauer, Markus Biberacher, Thomas Blaschke
Date Published: 2016
DOI: 10.1080/09640568.2015.1044652
Sponsors:
Austrian Science Fund (FWF)
Platforms:
Python
Model Documentation:
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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.
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