How Sample works

If the input locations are specified as a point feature dataset, the point coordinates may not be the same as the cell centers of the cells specified in the input raster. To determine the values at the exact locations of the selected points, a resampling technique must be adopted. For discrete data types, the default NEAREST resampling algorithm will be satisfactory. However, for continuous data types, it is more appropriate to perform another resampling technique. For instance, for elevation data, applying bilinear interpolation or cubic convolution will provide more accurate results. The bilinear option will determine the cell values based on a weighted distance of the four nearest input cell centers. The cubic option will compute the cell value based on the weighted distance of the nearest 16 cells.

For each selected cell, information on the selection zone number, location in map space (x,y coordinates), and cell values from each of the input rasters is written to the table. The output is organized by the zone of the Input location raster or point features (the raster value or point feature ID). The table has the following structure:

   zone# x,y cellvalue1 cellvalue2 cellvalue3 ....
   zone# x,y cellvalue1 cellvalue2 cellvalue3 ....

The zone number will be equal to zero when the input specified for the locations is a feature point dataset.

An example of the table output from the Sample tool follows:

   60 397293 458861 60 74 74.5
   60 397344 458869 60 76 74.5
   40 397393 458811 MISSING 72 74.5
   60 397293 458812 32 74 74.5
   60 397345 458818 MISSING MISSING 74.5
   57 397449 458813 44 72 74.5