Neighborhood Operations in Raster Data: Focal Operation and Moving Window (Especially for GATE-Geospatial 2022)

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A neighborhood operation involves a focal cell and a set of its surrounding cells. The surrounding cells are chosen for their distance and directional relationship to the focal cell.

Focal Operation

The focal operation is a spatial function that computes an output value of each cell using neighborhood values. Convolution, kernel and moving windows are examples of image processing techniques that use focal operations.

Neighborhood Analyst > Neighborhood Statistics

Moving Window

A moving window is a rectangular arrangement of cells that applies an operation to each cell in a raster dataset while shifting in position entirely.

Figure Shows Moving Window in Neighborhood Operation

A neighborhood operation is a spatial function where the output location, area and extent come from areas larger than and adjacent to the input cells. For example, average neighborhood operations smooth values in a map. Common neighborhoods include rectangles, circles, annuluses, and wedges. The neighborhood functions are of two types:

Diagram Shows Two Types of Neighborhood Functions

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