Since the values can change, Bilinear is not recommended for categorical data. This means that the output value could be different than the nearest input, but is always within the same range of values as the input. The closer an input cell center is to the output cell center, the higher the influence of its value is on the output cell value. Nearest Neighbor can be used on continuous data but the results can be blocky.īilinear Interpolation uses a weighted average of the four nearest cell centers. The value of of the output cell is determined by the nearest cell center on the input grid. The values that go into the grid stay exactly the same, a 2 comes out as a 2 and 99 comes out as 99. Nearest Neighbor is best used for categorical data like land-use classification or slope classification. The method used depends upon the input data and its use after the operation is performed. The three resampling methods Nearest Neighbor, Bilinear Interpolation and Cubic Convolution, determine how the cell values of an output raster are determined after a geometric operation is done. Photo by Dave Gandy under the Public Domain Dedication License
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