Legend Build enables you to create automatically classified legends without using the legend editor. Compared to using the legend editor Legend Build has the following advantages:

• Classification of multiple themes with the same method in one step.
• Classification of floating point grids (may need longer calculation time because the grids are divided in 65535 classes).
• Creation of legends with defined class width. The number of classes results from the defined class width, not vice versa.
• Defining the minimum and the maximum value of a classification (upper and lower border). Smaller respectively bigger values can either be ignored or be grouped in an open class. For grid themes this option needs longer calculation time. If the minimum value is chosen bigger than the maximum value, the classification is reversed (i.e. it starts with the maximum value).
• If the number of colors is different from the number of classes, either the surplus colors are removed or the missing colors repeated in order to create continous color ramps (see Colors Ramp).

The following input is necessary:

• The themes which legends shall be created must be active.
• Classification field: If the active theme does not have a classification field (legend type Single Symbol) you have to choose one. It should contain those values you want the theme to be classified with.
• Colors: Choose the color scale you want to use. The number of colors is automatically adapted to the number of classes and continuous colors are created.
• Current Colors: Keep the current colors.
• ArcView Colors: Choose a pre-defined ArcView color scale.
• Theme Colors: Use the colors of any other theme.
• Legend File: Load colors from any existing legend file.
• Flip Order: The order of the color scale will be reversed.
• Classification Type: Choose the classification method. Not only the ArcView default methods Quantile, Equal Area, Natural Breaks, Equal Interval, Standard Deviation but also the new Method Fixed Interval for fixed class widths is supported (see below).
• Classes: Input depending on classification method.
• Class Width: If using Fixed Interval the Class Width must be defined.
• Break Classes at: Enter the division factor of the standard deviation If using StdDev the Dividing Factor of the Standard Deviation must be defined (see description of the classification methods below).
• Number of Classes: Using all other methods, the Number of Classes must be defined.
• Round Values at: Number of digits the values should be rounded at.
• Unit String: Enter a text that should be added to the label of all classes (normally a measure like m or %).
• Limit Data Range: The data is not restricted without defining it.
• Enter the Minimum Value: Define the lower limit of the first class (default value is the minimum value of the first theme). Smaller Values: Collect the values below the chosen limit, which are ignored otherwise, to an open class.
• Enter the Maximum Value: Define the upper limit of the last class (default value is the maximum value of the first theme). Larger Values: Collect the values below the chosen limit, which are ignored otherwise, to an open class.
• Outline: The outline color of the created classes can be chosen (only relevant for polygon themes). By deactivating this option the outline is deactivated.
• NoData: The color of the NoData class can be chosen (these contains all missing values). By deactivating this option the empty values are displayed transparent.

• Quantile: Create classes with the same number of values in each class (at grid themes this corresponds with the size of the area). This is the simplest classification method and only suitable for linear distributed data. At disproportionate distribution others are to be preferred.
• Equal Area: Split the total area into classes of same size (according to polygon area, line length or number of points or cells). Each class contains approximately the same area but not always the same number of elements. Only if the size of the elements is approximately the same, this method produces the same results as Quantile.
• Natural Breaks: Create the desired number of classes by defining "natural" class limits. By matters of a statistic formula (so called Jenk's Optimization) the sum of variances in each class is minimized. This method is rather complex but gives normally the best results, because it finds groupings and patterns inherent in the data. The calculation is done by the number of elements - the area of the elements is only considered at grid themes (number of cells). At very unproportioned distribution of the areas of polygon themes Equal Area should be preferred.
• Equal Interval: Create the desired number of classes with the same width (between minimum and maximum value). The number of classes can be defined - the width is resulting.
• Fixed Interval: This additional in Arc4You implemented classification method creates classes with the desired class width (between minimum and maximum value). The width of the classes can be defined, the number of classes is resulting.
• Standard Deviation: With this method you can calculate the average value of the data and show it as the central class "mean" (which normally doesn't contain data). Above and below classes with a fraction of the standard deviation (this factor can be defined - normally ¼, ½ or 1) as a class width are created until all data values are included. The classification can therefore also be asymmetric i.e. contain a differing number of classes above and below. All values above or below of the triple standard deviation will be collected in an open class each. It is recommended to use a dichromatic color scale.