Andrew Farrow

A method and application of multi-scale validation in spatial land use models

The majority of the large number of existing land use models lack a proper validation, often because of data problems. Moreover, despite recognition of the necessity to incorporate a multi-scale analysis, scale dependencies are normally not considered during validation. In this paper, a multi-scale land use change modelling framework, conversion of land use and its effects (CLUE), is calibrated for Costa Rica and validated at five spatial resolutions for Honduras and Costa Rica. Both countries experienced locally very strong actual land use changes. Calibration runs show that the model is very sensitive to changes in the autonomous development parameter, which defines the influence of the finest resolution. Validation results are very satisfactory for both countries. Especially, changes in major land use types are reproduced with the model. Changes in localised land use types are more difficult to project. The magnitude of gains and magnitude of losses are slightly underestimated in all cases. The multi-scale validation demonstrates that results improve strongly, and exponentially, with decreasing spatial resolution. Strong reduction of the number of observations results in a correlation between actual and modelled changes that approximates the perfect value of 1. The study demonstrates that the CLUE modelling framework can reproduce changes as they took place in Central America in the 1970s and 1980s, and shows how conclusions can differ depending on the scale at which validation is performed.

Land use modelling at the regional scale : an input to rural sustainability indicators for Central america

Abstract The monitoring of rural development and land use is a key requirement in order to produce information for policy-makers and planners and aid their understanding of development processes. Environmental and sustainability indicators, when combined with tools for their visualisation, manipulation and analysis are essential components of the monitoring process. By providing these information products and tools policy-makers can be given the opportunity to spatially interrogate the driving forces and the current state of rural development. However it is also vitally important for decision-makers to understand how trends will develop in the short-term future and the possible impacts of their decisions on the development process. This paper shows how the results of a spatially explicit land use model have been incorporated into a set of rural sustainability indicators to provide information to policy-makers in a form consistent with the information used in the monitoring process. The success of the monitoring process will depend not only on the availability of tools and indicators but also on the skills of the users and an institutional framework that fosters the application of these skills. Reliable and harmonised data are the key to obtaining useful results from the land use model chosen for this study, however responsibility for these data lies with the appropriate institutions in the countries of Central America. Demonstrating what can be done with ‘their’ data may provide these institutions with the necessary justification to overcome a lack of political will to invest in data collection, data use and the implementation of standards.