Calibration and validation of land-use models

Land use is constantly changing. For example, urban areas expand as a result of population growth, cropping patterns change to fulfil the demand for bioenergy and natural vegetation recovers in locations where farmers cease to farm. Understanding these changes is pivotal to explore future land-use scenarios and to design spatial policies. Land-use models are increasingly being used for these purposes. They function as virtual laboratories in which scientists or policy analysts can conduct experiments. In order to reliably apply models for these purposes, they need to be calibrated, where calibration is the adjustment of parameters to improve the model’s performance. Consequently, the value of modelled land-use scenarios and policy assessments depends on the quality of the calibration. Assessment of the quality of the calibration is termed validation, and is ideally performed independently in the sense that the data that is used for validation has not been used for calibration. The development of a land-use model can be described by four sequential phases: analysis and conceptual modelling, computer programming of the conceptual model, calibration of the computerized model, and experimentation with the calibrated model. The first three phases all have their own evaluation procedures: conceptual validation, code verification and operational validation, respectively. Operational validation provides insights into the strengths and weaknesses of a particular model application, and sometimes it can suggest directions for improvement. However, available assessment methods have limitations for their application in land-use modelling. Therefore, there is a demand to develop and apply more appropriate methods. The work presented in this thesis first considers the properties of land-use models that are important for their assessment, and subsequently presents and applies several methods that can be used for this assessment. Many land-use changes are directly or indirectly the