1. Using Raster Calculator statements to simplify data
    (previous page)
  2. Using a Reclassify operation (Spatial Analyst Menu Reclassify or Reclassify and Slice tools)
    This is referred to sometimes as a density slice or simply “slice,” and reduces data to usable information.

    1. It can be used with binary, multiple, and index layers.
      1. Choose the number of classification bins (the example below is 5 classes)
      2. Choose how you want the histogram divided (here is some ESRI help on how these methods work) The two most common methods are equal interval and equal area (known in ESRI-speak as “quantile”). The illustration above uses “equal interval.” These choices are also available for symbology of any layer (without changing the data)

        These are the choices from the Reclassify tool, and similar choices are found in the Slice tool. The reclassification you choose has a huge impact on the nature of the output. Note the change in results and histograms from the data found in simplify project (to see the effect, I created histograms for the different reclass types illustrated below left in an older version of the software. I don’t think you can do this anymore).
    2. Reclassify is the only good way to deal with discrete, non-numeric layers (like land use, e.g., pasture, roads, forest, lakes, etc) that have to be combined by hand (“manual” reclassification”)
    3. Metadata are complicated. If you use a toolbox, it creates the geoprocessing history, but it is impossible to recover and difficult to read in that format (try it). Better to save the reclassification scheme directly from the tool, by clicking the “save” button. This operation stores an ArcMap table. You must highlight the classes you want to save before you save, or the table will be empty (way to go ESRI).
  3. Lastly, Query operations (perhaps multiple ones) can be used to reclassify. This is an uncommon, labor intensive method to select criteria or input.
    1. each separate category must be saved independently (for example, each of the four possible combinations of two binary layers)
    2. more useful across multiple map layers (see next page)