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A method for exploiting the nonlinear structure of hyperspectral imagery employs a manifold coordinate system that preserves geodesic distances in the high-dimensional hyperspectral data space. Data representing physical parameters such as a scene is divided into a set of smaller tiles. The manifolds derived from the individual tiles are then aligned and stitched together to complete the scene. Coordinates are derived for a very large although not complete representative subset of the data termed the “backbone”. Manifold coordinates are derived for this representative backbone and then the remaining samples inserted into the backbone using a reconstruction principle using the property of local linearity everywhere on the manifold to reconstruct the manifold coordinates for the samples not originally belonging to the backbone. The output is a global manifold coordinate system, which for topographical image data depicts clearer detail of land and water portions of a scene.