Comparison of Two Common Empirical Methods to Model Land-Use Choices in a Multi-Agent System Simulation of Landscape Transition: Implication for a Hybrid Approach

Land-use choice routines embedded in a human-environment system (HES) model must meet more requirements than those in models typically presented in purely economic or psychological studies. This study compares the strengths and shortcomings of two common empirical methods multi-nominal logistic (MNL) regression and classification tree (CT) analysis – for specifying landuse choices in a multi-agent system simulation framework (Land Use Dynamics Simulator LUDAS). First, we described design concepts of land-use decisionmaking mechanism in the LUDAS framework in which household’s land-use choice is a component. Next, we compared two common methods for modeling the landuse choice with respect to pre-established criteria: a MNL model was specified to represent assumed rational behavior of human agents, while the CT model used a data-fit hierarchical rule set to represent heuristic process of reflex behavior. The study was conducted based on an intensive household-farm survey in a Central Vietnam’s mountainous catchment. Based on the comparative analysis, we recommended explicit strategies for developing structurally realistic models that utilizes the complementarities of the both techniques to better represent bounded rational, yet adaptive, land-use choices in a HES model in the face of uncertainty.