The input imagery layer containing multidimensional data that will be aggregated.

The aggregation dimension. This is the dimension along which the variables will be aggregated.

The variable or variables that will be aggregated along the given dimension. If no variable is specified, all variables with the selected dimension will be aggregated.

For example, to aggregate daily temperature data into monthly average values, specify temperature as the variable to be aggregated. If you do not specify any variables and you have both daily temperature and daily precipitation variables, both variables will be aggregated into monthly averages and the output multidimensional raster will include both variables.

Specifies the mathematical method that will be used to combine the aggregated slices in an interval.

• Mean—The mean of a pixel's values across all slices in the interval will be calculated. This is the default.
• Maximum—The maximum value of a pixel across all slices in the interval will be calculated.
• Majority—The value that occurred most frequently for a pixel across all slices in the interval will be calculated.
• Minimum—The minimum value of a pixel across all slices in the interval will be calculated.
• Minority—The value that occurs least frequently for a pixel across all slices in the interval will be calculated.
• Median—The median value of a pixel across all slices in the interval will be calculated.
• Percentile—The percentile of values for a pixel will be calculated across all slices in the interval. The 90th percentile is calculated by default. You can specify other values (from 0 to 100) using the Percentile value parameter.
• Range—The range of values for a pixel across all slices in the interval will be calculated.
• Standard Deviation—The standard deviation of a pixel's values across all slices in the interval will be calculated.
• Sum—The sum of a pixel's values across all slices in the interval will be calculated.
• Variety—The number of unique values of a pixel across all slices in the interval will be calculated.
• Custom—The value of a pixel will be calculated based on a custom raster function template.

Specifies the dimension interval for which the data will be aggregated.

• All—The data values will be aggregated across all slices. This is the default.
• Interval Keyword—The variable data will be aggregated using a commonly known interval.
• Interval Value—The variable data will be aggregated using a user-specified interval and unit.
• Interval Ranges—The variable data will be aggregated between specified pairs of values or dates.

Specifies the keyword interval that will be used when aggregating along the dimension.

• Hourly—The data values will be aggregated into hourly time steps, and the result will include every hour in the time series.
• Daily—The data values will be aggregated into daily time steps, and the result will include every day in the time series.
• Weekly—The data values will be aggregated into weekly time steps, and the result will include every week in the time series.
• Monthly—The data values will be aggregated into monthly time steps, and the result will include every month in the time series.
• Quarterly—The data values will be aggregated into quarterly time steps, and the result will include every quarter in the time series.
• Yearly—The data values will be aggregated into yearly time steps, and the result will include every year in the time series.
• Recurring Daily—The data values will be aggregated into daily time steps, and the result will include one aggregated value per Julian day. The output will include, at most, 366 daily time slices.
• Recurring Weekly—The data values will be aggregated into weekly time steps, and the result will include one aggregated value per week. The output will include, at most, 53 weekly time slices.
• Recurring Monthly—The data values will be aggregated into weekly time steps, and the result will include one aggregated value per month. The output will include, at most, 12 monthly time slices.
• Recurring Quarterly—The data values will be aggregated into weekly time steps, and the result will include one aggregated value per quarter. The output will include, at most, 4 quarterly time slices.
• Dekadly— The data values will be aggregated into 3 periods of 10 days each. The last period may contain more or fewer than 10 days. The output will include 3 slices for each month.
• Pentadly—The data values will be aggregated into 6 periods of 5 days each. The last period may contain more or fewer than 5 days. The output will include 6 slices for each month.

This parameter is required when the aggregation definition is set to Interval Keyword, and the aggregation is across time.

The size of the interval that will be used for the aggregation. For example, to aggregate 30 years of monthly temperature data into 5-year increments, enter 5 as the Value Interval value, and set the Unit parameter to Years.

This parameter is required when the aggregation definition is set to Interval Value.

The unit that will be used for the interval value.

This parameter is required when the aggregation definition is set to Interval Value, and the aggregation is across time.

Interval ranges will be used to aggregate groups of values. They consist of pairs of minimum and maximum range values, with data type Double or Date.

This parameter is required when the aggregation definition is set to Interval Ranges.

Specifies whether missing values are ignored in the analysis.

• Checked—The analysis will include all valid pixels along a given dimension and ignore any NoData pixels. This is the default.
• Unchecked—The analysis will result in NoData if there are any NoData values for the pixel along the given dimension.

The name of the layer that will be created in My Content and added to the map. The default name is based on the tool name and the input layer name. If the layer already exists, you will be prompted to provide another name.

You can specify the name of a folder in My Content where the result will be saved using the Save result in drop-down box.

The percentile to calculate. The default is 90, indicating the 90th percentile.

The values can range from 0 to 100. The 0th percentile is equivalent to the minimum statistic, and the 100th percentile is equivalent to the maximum. A value of 50 will produce the same result as the median statistic.

Specifies the method of percentile interpolation that will be used when there is an even number of values from the input raster to be calculated.

• Nearest—The nearest available value to the desired percentile will be used. In this case, the output pixel type will be the same as that of the input value raster.
• Linear—The weighted average of the two surrounding values from the desired percentile will be used. In this case, the output pixel type will be floating point.