This paper describes an image patch characterization for image information mining tasks. An image patch is first decomposed into a multi-scale segmentation thanks to the Max Tree representation. Then, each segment is described by shift invariant shape attributes. Finally, the segment attributes are aggregated into a shape distribution which constitutes the patch characterization. Illustrations of this image content description are given for patches of a WorldView-2 multi-spectral scene, and the information relevance is assessed by an automatic classification of the patch characteristics which is compared to land use/land cover annotations.