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Murtaugh, P., and D. L. Phillips. 1998. Temporal correlation of classifications in remote sensing. Journal of Agricultural, Biological, and Environmental Statistics 3(1):99-110

A bivariate binary model is developed for estimating the change in land cover from satellite images obtained at two different times. The binary classification of a pixel at the two times are modeled as potentially correlated random variables, conditioned on the true states of the pixel. The model can be fit into a "training" set of pixels for which the true states are presumed from a reference dataset, and two methods are proposed for using the results of that fit to predict the true states in a separate set of pixels having only classification information. Applied to two images taken over Mexico by the LANDSAT Multi-Spectral Scanner, this methodology finds statistically significant temporal correlation of pixel classifications and illustrates that adjustment for this correlation is important for obtaining accurate estimates of changes in land cover.

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