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Assessing the significance of global and local correlations under spatial autocorrelation;a nonparametric approach
Geostatistics Monte-Carlo methods Resampling Spatial autocorrelation Spatial statistics Variogram
2015/8/21
In this paper we present a method to assess the significance of the correlation coefficient when at least one of the variables is spatially autocorrelated. The standard test assumes independence of th...
A Directional Gradient-Curvature Method for Gap Filling of Gridded Environmental Spatial Data with Potentially Anisotropic Correlations
correlation anisotropy spatial interpolation stochastic estimation optimization simulation
2013/4/27
We introduce the Directional Gradient-Curvature (DGC) method, a novel approach for filling gaps in gridded environmental data. DGC is based on an objective function that measures the distance between ...
Enhancing hyperspectral image unmixing with spatial correlations
Bayesian inference Monte Carlo methods spectral unmixing hyperspectral images Markovrandom fields Potts-Markov model
2010/3/10
This paper describes a new algorithm for hyperspectral image unmixing. Most of the unmixing
algorithms proposed in the literature do not take into account the possible spatial correlations
between t...