Modélisations prospectives de l’occupation du sol. Le cas d’une montagne méditerranéenne

Abstract

The authors apply three methods of prospective modelling to high resolution georeferenced land cover data in a Mediterranean mountain area: GIS approach, generalized linear model and neural networks. Land cover prediction to the latest known date is used to validate the models. In the frame of spatial-temporal dynamics in open systems, results are encouraging and comparable. Correct prediction scores average around 73 %. The results analysis focuses on geographic location, land cover categories and parametric distance to reality of the residuals. Comparing the three models shows the high degree of convergence and a relative similitude of the results obtained by the two statistical approaches compared to the GIS supervised model. Further steps are the application of the models to other test areas and the identification of respective advantages to develop an integrated model.

Keywords

• GIS
• forecast
• generalized/generalised linear model
• Eastern Pyrenees