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TEMPORAL CORRELATION OF CLASSIFICATIONS IN REMOTE SENSING
Citation:
Murtaugh, P. A. AND D. Phillips. TEMPORAL CORRELATION OF CLASSIFICATIONS IN REMOTE SENSING. Journal of Agricultural Biological and Environmental Statistics 3(1):99-110, (1998).
Description:
A bivariate binary model is developed for estimating the change in land cover from satellite images obtained at two different times. The binary classifications of a pixel at the two times are modeled as potentially correlated random variables, conditional on the true states of the pixel. The model can be fit to a "training" set of pixels for which the true states are presumed from a reference dataset, and two methods are proposed for using the reults 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.