Modelling the impacts of land system dynamics on human well-being: Using an agent-based approach to cope with data limitations in Koper, Slovenia

To cope with data limitations and to provide insight into the dynamics of LUCC for local stakeholders in the Municipality of Koper, Slovenia, we constructed an ABM (loosely defined) that integrates utility theory, logistic regression, and cellular automaton-like rules to represent the decision-making strategies of different agents. The model is used to evaluate the impact of LUCC on human well-being, as represented by the provision of highly productive agricultural soil, the extent of noise pollution, and quality-of-life measurements. Results for the Municipality of Koper show that, under a range of model assumptions, (1) high quality agricultural soils are disproportionately affected by urban growth, (2) aggregate resident quality of life increases non-linearly with a change in development density, (3) some drivers of residential settlement produce non-linear preference responses, and (4) clustering industrial development had a beneficial impact on human well-being. Additional novel contributions include the incorporation of noise pollution feedbacks and an approach to empirically inform agent preferences using a conjoint analysis of social survey data.

► We model land-use change using an ABM approach to cope with data constraints. ► We assess the impacts of land-use dynamics on human well-being in Koper, Slovenia. ► Regression, cellular automata, and utility models represent agent decisions. ► The integrative data and modelling aspect of ABM to study land-use change is shown.