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majority resampling
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[statistics]
A technique for resampling raster data in which the value of each cell in an output is calculated, most commonly using a 2x2 neighborhood of the input raster. Majority resampling does not create any new cell values, so it is useful for resampling categorical or integer data, such as land use, soil, or forest type. Majority resampling acts as a type of low-pass filter for discrete data, generalizing the data and filtering out anomalous data values.