Abstract:The accuracy in land-cover classification using remotely sensed imagery can be increased using Bayesian methods that incorporate prior probabilities of classes. However, estimating these prior probabilities can be expensive and data intensive. We propose methods to improve the classification accuracy using Bayesian methods to classify ambiguous (or low-confidence) pixels, using only the remotely sensed imagery or existing land-cover maps to estimate prior probabilities. We propose a spatial method that predict… Show more
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