Land-use-change patterns are the result of the complex interaction between the human and the physical environment. Case studies of the determinants of land-use change can help to analyse which theory is appropriate in a particular region and stimulate the development of new theoretic understandings. In this paper an empirical method is presented to analyse the pattern of land-use change that allows a wide range of factors, from different disciplines, to contribute to the explanation of land-use change. The method is applied to the Netherlands, based on an extensive database of land-use change and its potential determinants. Historic as well as recent land-use changes are studied. Historic land-use change is related mainly to the variation in the biophysical environment. Levels of explanation are low because of the inability to address the temporal variation in location factors. For the recent changes in land use high levels of explanation are obtained. The most important changes during this period are expansions of residential, industrial/commercial, and recreational areas. The location of these changes can be explained by a combination of accessibility measures, spatial policies, and neighbourhood interactions. On the basis of these results it is possible to define priority topics for in-depth analysis of land-use-change processes and suggest factors, relations, and processes that need to be included in dynamic land-use-change models that support land-use-planning policies.

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Activity-based accessibility measures, describing the level of access to spatially distributed activities, are not put to the same use in land use and/or transport policy evaluations as are infrastructure-based accessibility measures, which describe congestion levels or the average speed on the motorway network. In this paper we attempt to improve the current evaluation practice by the application of potential, activity-based, accessibility measures for the analysis of job accessibility, using existing traditional land-use and transport data and/or models. We try to improve the interpretability of the results by estimating the separate influence of land-use changes, infrastructure projects, and congestion on the development of job accessibility. A case study of the Netherlands shows the importance of incorporating job competition and the match between educational and job levels in the analysis of job accessibility.