Available with Spatial Analyst license.

Available with 3D Analyst license.

The Reclass geoprocessing functions provide a variety of methods that allow you to reclassify or change input cell values to alternative values.

The most common reasons for reclassifying data are to accomplish the following:

- Replace values based on new information.
- Group certain values.
- Reclassify values to a common scale (for example, for use in a suitability analysis or for creating a cost raster for use in the Cost Distance geoprocessing function).
- Set specific values to NoData or set NoData cells to a value.

There are several approaches to reclassifying your data. The methods of reclassification and the geoprocessing functions that perform them are:

- Individual values. (Lookup, Reclassify)
- Ranges of values. (Reclass by ASCII File, Reclass by Table, Reclassify)
- Intervals. (Slice)
- Continuous values using functions. (Rescale by Function)

The following topics provide background information on the theoretical aspects of these geoprocessing functions as well as some examples of their implementation.

- Learn how to reclass by individual values
- Learn how to reclass by ranges of values
- Learn about reclassification tables
- Learn how to group values into intervals or by area
- Learn how to rescale continuous data using functions

The following table lists the available geoprocessing functions and provides a brief description of each.

Geoprocessing Function | Description |
---|---|

Creates a raster by looking up values in another field in the table of the input raster. | |

Reclassifies (or changes) the values of the input cells of a raster using an ASCII remap file. | |

Reclassifies (or changes) the values of the input cells of a raster using a remap table. | |

Reclassifies (or changes) the values in a raster. | |

Rescales the input raster values by applying a selected transformation function and transforming the resulting values onto a specified continuous evaluation scale. | |

Slices or reclassifies the range of values of the input cells into zones (classes). The available data classification methods are equal interval, equal area (quantile), natural breaks, standard deviation (mean-centered), standard deviation (mean as a break), defined interval, and geometric interval. |