Land Use Mapping Using Constrained Monte Carlo Methods
We present a flexible, automated, Bayesian method designed for broad scale land use mapping. The method is based on a Monte Carlo Markov Chain and integrates a number of sources of ancillary data. It produces a probability density over a finite set of land use classes that can be used directly in further analyses or to classify individual pixels. The method assumes a multi- nomial prior over the possible land use types, and uses agricultural...[Show more]
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