Improving the landcover classification using domain knowledge

This paper deals with the integration of domain knowledge to improve the la ndcover classification of a sequence of images. This new approach consists in representing the plot of land as a dynamic system and in modelling its e volution (knowledge about crop cycles, rotations and farmer practices) with the timed automata formalism. The main feature of this work is to improve the classification provided by a traditional classification with data resul ting from the simulation of the plot evolution model. The aim of this paper is to focus on the experiments carried out on a sequence of five images. T he problem of classification refinement and the model used to capture domai n knowledge are first presented. The emphasis is then put on the results an d their interpretation that show the contribution of the method to improve the classification of images.