Question

Describe the difference between a local function and a neighborhood function in raster data analysis.

Answer 1

• Local functions

Most grid operations perform their algorithm on every cell in the dataset. You can think of the local function calculation engine as starting at once cell location, performing a calculation once on the inputs at that location, and then moving on to the next cell location, and so on.

Here is a local function, where the individual output grid cell values are the result of the local sine function performed on every input cell:

Most of the functions that create new grids based on analyses performed on vector layers are local functions.

• Focal functions

Certain grid operations do consider neighborhoods, so that the output cell is the result of a calculation performed on either a group of cells determined by a window of cells (known as a kernel or focus) around the cell of interest. These operations are called focal functions. For example, a smoothing (low-pass filter) algorithm will take the mean value of a 3-x-3 cell kernel, and place the output value in the location of the central cell. If the kernel contains locations that are outside of the grid, these locations are not used in the calculation.

In this focal mean example, the outlined cells in the input grid are averaged, and the resultant value is placed in the center cell of the kernel in the output grid. This is done for every 3-x-3 neighborhood in the input.