  In this paper we address the problem of change detection in multi-spectral
images by proposing a data-driven framework of graph-based data fusion. The
main steps of the proposed approach are: (i) The generation of a multi-temporal
pixel based graph, by the fusion of intra-graphs of each temporal data; (ii)
the use of Nystr\"om extension to obtain the eigenvalues and eigenvectors of
the fused graph, and the selection of the final change map. We validated our
approach in two real cases of remote sensing according to both qualitative and
quantitative analyses. The results confirm the potential of the proposed
graph-based change detection algorithm outperforming state-of-the-art methods.
