Agent-based modelling of land use dynamics and residential quality of life for future scenarios

Scenario-based analysis has previously been applied to Land Use and Land Cover  Chance (LUCC) by defining a coherent set of possible future developments. Typically, computational models are therein used to interpret qualitative future storylines in terms of quantitative future impacts. In the following paper, we address challenges and illustrate advantages of a scenario based approach using Agent-Based Modelling. We show how storylines are useful to integrate a broad variety of knowledge sources, such as subjective expert knowledge and results from other (integrative) models, which rely on a similar set of future assumptions. We also demonstrate the advantages of Agent-Based Models (ABMs) for interpreting future scenarios in the context of spatial and temporal variations in socio-ecological outcomes based on heterogeneous individual behaviour. For example, we show how ABMs enable us to identify hotspots of future development and LUCC. Furthermore, we illustrate a procedure for downscaling and interpreting storylines from general qualitative trends to local quantitative parameters within an ABM framework. We apply this framework to the Municipality of Koper, Slovenia, where we measure future impacts of LUCC on the loss of agricultural land and residential quality-of-life (QoL). We compare our results to a ``business-as-usual'' baseline and we show that industrial and commercial development has the greatest impact on the loss of high quality agricultural land across all scenarios. Furthermore, our models indicate an increase in inequality in the perceived quality-of-life, with the new residential areas outperforming the existing ones.