Available with Spatial Analyst license.
The generalization analysis tools are used to either clean up small erroneous data in the raster or generalize the data to get rid of unnecessary detail for a more general analysis.
There are several common sources for the erroneous data, such as the following:
- Classified satellite imagery may contain many small areas of misclassified cells.
- Images that are scanned paper maps may contain unnecessary lines or text.
- Conversion issues from rasters in different formats, resolutions, or projections may exist.
The generalization tools help you identify such areas and automate the assignment of more reliable values to the cells that make up the areas.
The generalization tools are divided into several general categories:
- Those that generalize on zones.
(Expand and Shrink, as well as Nibble and Thin)
- Those that smooth zone edges.
(Boundary Clean and Majority Filter)
- Those that identify the unique regions that comprise zones.
- Those that alter the resolution of the data.
The following table lists the available Generalization tools, and provides a brief description of each.
Generates a reduced-resolution version of a raster. Each output cell contains the Sum, Minimum, Maximum, Mean, or Median of the input cells that are encompassed by the extent of that cell.
Smooths the boundary between zones by expanding and shrinking it.
Expands specified zones of a raster by a specified number of cells.
Replaces cells in a raster based on the majority of their contiguous neighboring cells.
Replaces cells of a raster corresponding to a mask with the values of the nearest neighbors.
For each cell in the output, the identity of the connected region to which that cell belongs is recorded. A unique number is assigned to each region.
Shrinks the selected zones by a specified number of cells by replacing them with the value of the cell that is most frequent in its neighborhood.
Thins rasterized linear features by reducing the number of cells representing the width of the features.