Hyperspectral sensors (HS) are next-generation optical sensors that have excellent spectroscopic performance with hundreds of spectral bands. Multispectral sensors (MS) are conventional optical sensors that have a few tens of spectral bands with high spatial resolution. This work aims to combine, the spectral information of the hyperspectral image with the spatial and spectral information of the multispectral image for automatic classification while considering spatial relationships between sources in low-spatial resolution data. The considered approach is validated first by using synthetic images from the USGS spectral library, but also using Hyperion sensor as hyperspectral image. And SPOT sensor as multispectral image, representing the region of Gabes Matmata in southern Tunisia.