Attribute reclassification

Reclassifying attributes is the technique in GIS and other database software of creating a new categorical attribute in a dataset by classifying features based on existing attributes or other criteria, such as location. The uses of reclassification include quickly updating cells when new information is available, compiling data for suitability analyses, and eliminating unneeded information by reclassifying cells as NoData. The goal is often to simplify the output data in order to aid the interpretation.

Quantitative Data
Quantitative data includes data that has measurable values. In terms of GIS, some examples of raster data that is quantitative could include the following: precipitation, population density, temperature, etc. One of the most classic examples of reclassifying attributes is regrouping large amounts of data (say the numbers 1-100) to be represented on the map by only 5 symbols (for example, the number 1 on the map would refer to those cells with data between 1 and 20).

Nominal Data
Reclassification can also be used on nominal fields. For example, a GIS user may wish to take five road types (interstate, highways, main roads, collectors, and neighborhood roads) and reduce them to two types by reclassifying interstates, highways, and main roads as 'major streets' and collectors and neighborhood roads as 'local streets'. In addition to simplifying attributes, the reclassify tool can be used to assign values of sensitivity, priority or preference to a raster. The reclassify tool can change nominal values (values that represent a class) to ratio or interval data so that it can relate to other data on a common scale. In a suitability analysis, data is usually reclassified to a scale of 1 to 10, giving higher values to the more suitable areas.

Raster Data
Reclassifying attributes can be especially helpful in analyzing raster attribute data, which is often interval or ratio data that is continuous. This is easily done by assigning values to bins or ranges. For example, a Digital Elevation Model that has unique elevation values for each cell can be reclassified and symbolized to show specific elevation ranges i.e., 1,000-1,200 feet.

Reclassification and Map-Making
Reclassification is helpful for the map-maker because he/she can reclassify data based on the theme of the map or the point that the map is trying to convey. For example, a large-scale map might show more categories than a small-scale map. If the map-maker wanted to project a large scale map to a smaller scale, he/she might decide to reclassify the data to have fewer categories in order to avoid complexity and confusion. By grouping attributes into a few discernible categories, the visual hierarchy of the map can be more clear.