Agent-based modelling is an approach that has been receiving attention by the land use modelling community in recent years, mainly because it offers a way of incorporating the influence of human decision-making on land use in a mechanistic, formal, and spatially explicit way, taking into account social interaction, adaptation, and decision-making at different levels. Specific advantages of agent-based models include their ability to model individual decision-making entities and their interactions, to incorporate social processes and non-monetary influences on decision-making, and to dynamically link social and environmental processes. A number of such models are now beginning to appear-it is timely, therefore, to review the uses to which agent-based land use models have been put so far, and to discuss some of the relevant lessons learnt, also drawing on those from other areas of simulation modelling, in relation to future applications. In this paper, we review applications of agent-based land use models under the headings of (a) policy analysis and planning, (b) participatory modelling, (c) explaining spatial patterns of land use or settlement, (d) testing social science concepts and (e) explaining land use functions. The greatest use of such models so far has been by the research community as tools for organising knowledge from empirical studies, and for exploring theoretical aspects of particular systems. However, there is a need to demonstrate that such models are able to solve problems in the real world better than traditional modelling approaches. It is concluded that in terms of decision support, agent-based land-use models are probably more useful as research tools to develop an underlying knowledge base which can then be developed together with end-users into simple rules-of-thumb, rather than as operational decision support tools.

Agent-based land-use models: a review of applications

Modeling human decisions in coupled human and natural systems: Review of agent-based models

Modelling land use change and environmental impact.

In spite of the many advances in land use and land cover change modelling over the past decade many challenges remain. One of these challenges relates to the explicit treatment of feedback mechanisms in descriptive models of the land use system. This paper argues for model-based analysis to explore the role of feedback mechanisms as determinants of land use dynamics and system evolution. Different types of feedbacks in the land use system are discussed addressing interactions over scales of analysis, feedbacks between impacts and driving forces of land use change and feedbacks between agents and land units. The inclusion of feedbacks in land use models will require new methods for model parameterization and calibration, but will ultimately increase our understanding of land use system dynamics.

Simulating feedbacks in land use and land cover change models

Land-use/cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. A common approach to analyse and simulate LUCC as the result of individual decisions is agent-based modelling (ABM). However, ABM is often applied to simulate processes at local scales, while its application in regional studies is limited. This paper describes first a conceptual framework for ABM to analyse and explore regional LUCC processes. Second, the conceptual framework is represented by combining different concepts including agent typologies, farm trajectories and probabilistic decision-making processes. Finally, the framework is illustrated through a case study in the Netherlands, where processes of farm cessation, farm expansion and farm diversification are shaping the structure of the landscape. The framework is a generic, straightforward approach to analyse and explore regional LUCC with an explicit link to empirical approaches for parameterization of ABM.

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An agent-based approach to model land-use change at a regional scale

A design and application of a multi-agent system for simulation of multi-actor spatial planning.

Individual-based models in the analysis of disease transmission in plant production chains: An application to potato brown rot

Technical documentation of a simulation model on brown rot dynamics in the Dutch potato production chain

Quarantine diseases comprise a distinct class of plant diseases. In contrast to other plant diseases, direct losses through crop damage are often limited. Yet, quarantine diseases may have serious economic consequences for a country as they threaten the country’s export of affected crops. In particular for this category of diseases, it is important to design a control strategy that is optimal from an epidemiological as well as an economic point of view. This chapter presents the development of a bioeconomic model to evaluate control strategies in terms of their cost-effectiveness, specified for brown rot in the Dutch potato production chain. The conceptual model consists of two modules: an epidemiological module, which is a stochastic, spatially explicit simulation model that simulates the spread of potato brown rot over all potato-growing farms and fields in the Netherlands, and an economic module, which calculates the total costs of brownrot prevalence, based on the results of the epidemiological model. The model is applied for two brown-rot policy scenarios, which differ in sampling frequency of harvested potato lots but are otherwise similar. The two scenarios are compared with respect to their effectiveness and efficiency. Concerning the costs of controlling brown rot, a low monitoring level appears to be more cost-efficient; however, when including expected export consequences, a high monitoring level may be preferable. The model presented here strongly facilitates the development of an optimal control strategy as it provides insight into the effectiveness of brown-rot control strategies in relation to their costs. Moreover, the introduced modelling concept can be a useful tool in analysing the epidemiological and economic effects of other (quarantine) diseases

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Evaluating the cost-effectiveness of brown-rot control strategies : development of a bio-economic model of brown-rot prevalence in the Dutch potato production chain

Dirk L. Kettenis

Papers

A design and application of a multi-agent system for simulation of multi-actor spatial planning.

Individual-based models in the analysis of disease transmission in plant production chains: An application to potato brown rot

Technical documentation of a simulation model on brown rot dynamics in the Dutch potato production chain

Evaluating the cost-effectiveness of brown-rot control strategies : development of a bio-economic model of brown-rot prevalence in the Dutch potato production chain