Work with multidimensional raster data

Multidimensional raster data can be visualized, explored, and analyzed in ArcGIS Pro.

Configure and load multidimensional raster data

Multidimensional mosaic datasets and .crf files can be added directly to ArcGIS Pro as layers to be visualized and processed in multidimensional analysis workflows. One or more variables can be added from NetCDF, GRIB, or HDF files and image services using the Add Multidimensional Raster Layers dialog box. The new raster layer contains the multidimensional information from the variables, which can be visualized, analyzed, and shared.

The Add Multidimensional Raster Layers dialog box provides multiple processing templates that control how your multidimensional raster data is configured in the map view.

Output configurationDescription

Multidimensional Raster

Selected variables will be added as individual multidimensional raster layers to the map view, one for each variable. This is the default.

Multidimensional Multivariate Raster

All selected variables will be added as a single multidimensional raster layer to the map view.

Vector Field (U-V)

U and V variables will be displayed as a U-V raster layer with arrows indicating the Vector-U value, the zonal or latitudinal velocity, and the Vector-V value, the meridional or longitudinal velocity. You must specify the variable for each value.

Vector Field (Magnitude-Direction)

Magnitude and direction variables will be displayed as a Magnitude-Direction raster layer, where the size of the arrows reflect the Vector-Magnitude value and the angle of the arrow represents the Vector-Direction value. You must specify the variable for each value, in addition to the Angle Reference System value.

Multiband Raster

All selected variables are composed in one multiband raster layer, with each band representing one variable.


Only .nc files that are compliant with NetCDF Climate and Forecast (CF) metadata standards are supported.

If your data is stored in an irregular grid and you are using the Multidimensional Raster or Multidimensional Multivariate Raster configuration option, use the Interpolate Irregular Data setting on the Add Multidimensional Raster Layers dialog box to interpolate your data into a regular grid.

When you need to manage a large number of multidimensional datasets, it is recommended that you add the variables to a mosaic dataset. See Multidimensional data in a mosaic dataset for details.

The steps to add multidimensional raster data to the map view are outlined below. It is assumed that you have scientific datasets in either netCDF, GRIB, or HDF format to use in these steps.

  1. On the Map tab, in the Layer group, click the Add Data drop-down menu and select Multidimensional Raster Layer. This opens the Add Multidimensional Raster Layers dialog box.
  2. On the dialog box, click the Import Variables drop-down menu Change Data Source to import variables from a file, multidimensional raster, multidimensional mosaic dataset, or image service. Choose the Import Variables from File option. The Import Variables From NetCDF, GRIB, or HDF files dialog box appears. Browse to a GRIB, netCDF, or HDF file. Alternatively, choose one of the other import options and browse to a multidimensional raster, mosaic dataset, or image service. Click Open to import variables from the selected file or dataset.
  3. On the Add Multidimensional Raster Layers dialog box, in the Select Variables table, select one or multiple variables.

    Add Multidimensional Raster Layers dialog box

  4. Choose an Output Configuration option and, optionally, the interpolation method, and click OK.

Create a Cloud Raster Format file

Esri's Cloud Raster Format (CRF) supports multidimensional raster data, and it is the primary data management structure for large multidimensional datasets, particularly when performing dimensional analysis such as temporal profiling. There are two ways to generate a CRF file.

If your multidimensional data is stored in a netCDF, HDF, or GRIB file, add the file as a multidimensional raster layer using the Add Multidimensional Raster Layers dialog box. To convert the layer to a .crf file, use the Copy Raster tool, set the output format to CRF and check the box to process the data as multidimensional. Optionally, you can build a multidimensional transpose.

If you have a series of images or rasters collected over time (and depth or height), you must first create a mosaic dataset and use the Add Rasters To Mosaic Dataset tool to add the time series of images or rasters to the mosaic dataset. Next, use the Build Multidimensional Info tool to generate variable and dimension information for the mosaic dataset. Finally, you can use the Copy Raster tool, set the output format to CRF and check the box to process the data as multidimensional, and optionally build a transpose.

For more information, see Managing multidimensional raster data.

Analyze and compute new variables

The Multidimensional Analysis toolset provides tools for analyzing multidimensional raster data, including trend analysis and change detection. The Multidimension toolset provides tools for managing multidimensional raster data, including merging and aggregating variables or dimensions.

Multidimensional raster layers can be processed and analyzed on the fly using raster functions. For example, you can use the Zonal Statistics function to calculate statistics for the multidimensional raster layer based on values within the zones of another dataset. See the complete List of Raster Functions for a summary of each raster function. In addition, you can chain the raster functions together and create custom raster function templates to calculate complex scientific equations. ArcGIS Pro provides the capabilities for distributed processing of imagery and scientific data using Raster analysis on Portal for ArcGIS. To take advantage of distributed processing capabilities, you need to configure your portal to perform raster analysis.

Publish multidimensional raster layers as web services

You can publish your multidimensional raster layers from ArcGIS Pro. Before publishing, consider the data source management structure to use, the number of services to publish, and the type of operations you want to perform on the services. For information on sharing your multidimensional raster data as an image service, see Share multidimensional raster data.

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