This tool can be used to identify an area of interest within a specified distance of features of interest in a raster data set.

The Euclidean distance (i.e. straight-line distance) is calculated between each grid cell and the nearest 'target cell' in the input image. Distance is calculated using the efficient method of Shih and Wu (2004). Target cells are all non-zero, non-NoData grid cells. Because NoData values in the input image are assigned the NoData value in the output image, the only valid background value in the input image is zero.

The user must specify the input and output image names, the desired buffer size (`size`), and, optionally, whether the distance units are measured in grid cells (i.e. `gridcells` flag). If the `gridcells` flag is not specified, the linear units of the raster's coordinate reference system will be used.

## Reference

Shih FY and Wu Y-T (2004), Fast Euclidean distance transformation in two scans using a 3 x 3 neighborhood, Computer Vision and Image Understanding, 93: 195-205.

## See Also

euclidean_distance

## Function Signature

`def buffer_raster(self, input: Raster, buffer_size: float, grid_cells_units: bool = False) -> Raster: ...`

## Project Links

WbW Homepage User Manual Support WbW