Classification Of Land Use Models

Different authors have provided reviews of land use models using classification systems, often based on the dominant technique used in the model or the underlying disciplinary theory. For deforestation models an overview is provided by Lambin (1997) and Kaimowitz and Angelsen (1998) while Miller et al. (1999) present a review of integrated urban models. Lambin et al. (2000) review models for agricultural intensification, Bockstael and Irwin (2000) review a number of land use models in terms of economic theory foundations. Agarwal et al. (2001) review 19 models based on their spatial, temporal and human-choice complexity. Briassoulis (2000) give an extended overview of all types of land use models. An overview of more recent approaches is provided by the special issues edited by the LUCC focus 3 office (Veldkamp and Lambin, 2001; Veldkamp and Verburg, 2004; Verburg and Veldkamp, 2005). In this chapter, we will focus on a short typology of model classes relevant to policy makers and discuss a number of features of land use systems that are central to land use change modelling.

The first broad distinction that can be made between different models is the difference between descriptive and prescriptive models. Descriptive models aim at simulating the functioning of the land use system and the spatially explicit simulation of near future land use patterns. Prescriptive models, in contrast, aim at the calculation of optimised land use configurations that best match a set of goals and objectives. Descriptive models are based on the actual land use system and dominant processes that lead to changes in this system. The model output provides insights in the functioning of the land use system and gives projections of LUCC for scenario conditions. Prescriptive models mostly include the actual land use system solely as a constraint for more optimal land use configurations. The basic objective of most prescriptive or optimisation models is that any parcel of land, given its attributes and its location, is modelled as being used in the way that best matches a series of defined objectives (Lambin et al., 2000). Prescriptive models are relevant to policy makers as a spatial visualization of the land use pattern that is the optimal solution based on their preferred constraints and objectives (Van Ittersum et al., 1998). However, prescriptive models do not provide insights in the actual land use change trajectories and the conditions needed to reach the optimised situation. Optimisation models suffer from other limitations, such as the somewhat arbitrary definition of objective functions and non-optimal behaviour of people, e.g., due to differences in values, attitudes and cultures. While, at an aggregate level, these limitations are likely to be nonsignificant, they are more important as one looks at fine scale land-use change processes and is interested in the diversity between actors (Lambin et al., 2000).

Another major difference between broad groups of land use models is the role of theory. While there is no single all-compassing theory of land use change, there are different, disciplinary, theories that can be used to describe land use change processes. Deductive models are based on theories and the results of model simulations are compared to actual land use changes to test the validity of the theory. The most classical land use change model based on economic theory is the Von Thunen model. Von Thunen's work is based on the concept of land rents which are closely related to the potential profit a farmer can make from growing a crop. As this profit is related not just to the value of a crop at the market but also to the cost to transport the products to that market, rent for any particular crop falls off with distance from the market. When farmers have a choice of crops to grow they will, obviously, chose the most profitable one. Spatially, this will result in a series of concentric rings around the market, with crops with the highest transport costs relative to the market price growing nearest to the city. More recent deductive models for agricultural expansion are presented by Angelsen (1999) who compares four different model specifications based on economic theory.

Inductive models are based on observed processes of land use change rather than based on a theoretical model. Different types of inductive models exist, ranging from models in which decision-making by actors is specified in a range of decision rules and interactions (e.g., Parker et al., 2003) to models in which the relation between land use location and variability in the socio-economic and biophysical environment is captured by statistical techniques, often regression (Geoghegan et al., 2001; Nelson et al., 2001; Verburg and Chen, 2000). Both inductive and deductive modelling informs us about the processes that lead to land use change. Whereas deductive models are able to test theories and the actual importance of a number of driving factors, inductive models suggest which drivers empirically are associated with land use patterns.

A final distinction between model types to be discussed in this chapter is the difference between static and dynamic models. The calculation of the coefficients of a regression equation explaining the spatial distribution of land use changes as a function of a number of hypothesized driving factors can be seen as a static model of LUCC (Chomitz and Thomas, 2003; Nelson and Hellerstein, 1997; Overmars and Verburg, 2005). Dynamic models often include temporal dynamics, in land use systems represented by competition between land uses, irreversibility of past changes and fixed land use change trajectories. Static models can be used to test knowledge about the driving factors behind land use change while dynamic models are essential when projections for future land use change are needed.

Any further classification of models would disregard the large group of models that combine different techniques and paradigms to integrate the different dimensions of land use change. Therefore, in the next section we will discuss the current capacity of models to simulate land use change based on a number of aspects that are considered most important in the study of LUCC:

• cross-scale dynamics;

• driving factors;

• spatial interaction and neighbourhood effects;

• temporal dynamics; and

• level of integration.

These features have been mentioned frequently in a series of recent papers, reports and workshops by members of the LUCC research community (Geist et al., 2001; Lambin et al., 2000; McConnel and Moran, 2001; Moran, 2005;

Ojima and Moran, 2004; Turner II et al., 1995; van der Veen and Rotmans, 2001; Veldkamp and Lambin, 2001).

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