Aggregate Multidimensional Raster

The Aggregate Multidimensional Raster tool generates a multidimensional raster dataset by combining existing multidimensional raster variables along a dimension.

Note:

To run this tool, the portal must be configured for raster analysis.

If you do not see this tool in Map Viewer, contact your portal administrator. Your portal may not be configured for raster analysis, or you may not have the privileges required to run the tool.

Workflow diagram

Example

Given 30 years of sea surface temperature data, collected monthly at every 5 meters depth up to 100 meters, aggregate data in the following ways:

• Aggregate monthly temperature data into yearly data.
• Aggregate monthly temperature data into 4-month intervals.
• Aggregate temperature data from 0 to 25 meters, then from 25 to 50 meters, and then from 50 to 100 meters.

Usage notes

This tool allows you to mathematically combine slices in a multidimensional dataset.

For information on how to publish multidimensional imagery layers, see Publish multidimensional imagery layers.

The parameters for this tool are listed in the following table:

Parameter	Explanation
Choose multidimensional imagery layer to aggregate	The input imagery layer containing multidimensional data that will be aggregated.
Choose dimension along which to aggregate	The aggregation dimension. This is the dimension along which the variables will be aggregated.
Choose variable(s) to aggregate	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.
Choose aggregation method	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. 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.
Choose aggregation definition	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.
Choose keyword interval	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.
Value interval	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.
Unit	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.
Define ranges	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.
Ignore missing values in calculation	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.
Result layer name	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.

Environments

Analysis environment settings are additional parameters that affect a tool's results. You can access the tool's analysis environment settings by clicking the gear icon at the top of the tool pane.

This tool honors the following Analysis Environments:

• Output coordinate system—Specifies the coordinate system of the output layer.
• Extent—Specifies the area to be used for analysis.
• Snap Raster—Adjusts the extent of the output so it matches the cell alignment of the specified snap raster layer.
• Cell size—The cell size to use in the output layer.
• Mask—Specifies a mask layer, where only the cells that fall within the mask area will be used for analysis.
• Resampling method—The method to use to interpolate pixel values.
• Recycle interval of processing workers—Defines how many image sections to process before restarting worker processes.
• Parallel processing factor—Controls the raster processing CPU or GPU instances.
• Number of retries on failures—Defines how many retries a worker process will attempt when there is random failure processing a job.

Similar tools and raster functions

Use Aggregate Multidimensional Raster to mathematically combine slices in a multidimensional raster. Other tools may be useful in solving similar problems.

ArcGIS Pro analysis tools and raster functions

The Aggregate Multidimensional Raster geoprocessing tool is available in the Image Analyst and the Spatial Analyst toolboxes.

Aggregate Multidimensional Raster is also available as a raster function.

ArcGIS Enterprise developers resources

If you are working in ArcGIS REST API, use the Aggregate Multidimensional Raster task.

If you are working in ArcGIS API for Python, use Aggregate Multidimensional Raster from the arcgis.raster.analytics module.