摘要： With the development of remote sensors, it is much easier to acquire large amount of remote sensing images (RSIs) with very high spatial resolution, which has made the spatial characteristics play an important role in classification task. Many work of spatial-spectral classification have been done and achieved good results, especially superpixel-based methods. However, these methods didn’t take each superpixel as an entirety, which had ignored the relationship between spatial and spectral signature. It is well known that RSI can be treated as a third-order data cube, thus it can also be represented by a third-order tensor. This paper proposed a Multi-Attribute Superpixel Tensor (MAST) model to address the aforementioned problem. Experiments conducted on two real RSIs and compared with several well-known methods demonstrate the effectiveness of the proposed model.