This paper presents the first results of a study devoted to the update of cartographic models with multispectral Spot images. With the current proliferation of GIS, this updating problem will be of prime importance in the next years. We first present the general issue and the tested application, which is limited to surfacic entities, small number of model classes, and registered images. The proposed methodology is inspired by previous research on image interpretation: the first step consists in the segmentation of the multispectral image in regions, the second step is a classification of these regions. We can improve the results of these two automatic steps by using the cartographic model, which remains mostly correct. The last step of the methodology is a probabilistic analysis of the changes between the model and the interpreted new image. The most probable changes are then proposed to the photo-interpretor as updating candidates. We show results for each step and describe possible improvements. The tests were done with extracts of the IGN BD-Carto, i.e. cartographic models with a few land-use classes: water, forest, urban... A validation procedure is currently undertaken by photo- interpretors, and their remarks will orient our future work.