Multidimensional data represents data captured at multiple times or multiple depths or heights. These data types are commonly used in atmospheric, oceanographic, and earth sciences. Multidimensional raster data can be captured by satellite observations in which data is collected at certain time intervals, or generated from numerical models in which data is aggregated, interpolated, or simulated from other data sources.
The common storage formats for multidimensional raster data are netCDF, GRIB, and HDF. Oceanographic data is often stored in netCDF format (.nc), weather data in GRIB format, and NASA often uses HDF format to store scientific data. These multidimensional formats share common capabilities for storing multiple variables, with each variable being a multidimensional array. Esri's Cloud Raster Format (CRF) and mosaic dataset also support multidimensional raster data storage. For example, multidimensional data can include temperature, humidity, and wind speed for every month from 2010 through 2020, and at elevations of 0, 1, and 10 meters, respectively. See Multidimensional raster types for more information.
ArcGIS Pro is capable of visualizing, managing, and processing multidimensional raster data, and publishing it as a web service. Adding a multidimensional raster layer to the map view allows you to explore your variables in one file, and the Multidimensional contextual tab provides an interactive experience for you to display the data slices you want and access the tools and functions for processing your multidimensional raster data quickly.
Managing multidimensional raster data
Multidimensional raster data is large and can be challenging to manage. The tools available in the Multidimension toolbox allow you to modify existing multidimensional rasters, generate multidimensional metadata in a mosaic dataset, transpose your data for optimized performance, and extract subset datasets. Multidimensional data management tools are available with an ArcGIS Pro license.
The CRF supports multidimensional raster storage and is the default output raster format for geoprocessing tools that generate mutidimensional rasters. The .CRF file is optimized for writing and reading large files in a distributed processing and storage environment. In a .CRF file, multidimensional raster data is divided into smaller bundles of tiles, which allows multiple processes to write simultaneously to an output.
When you work with a large number of multidimensional raster files with multiple variables, the multidimensional mosaic dataset is an effective way to store and manage your data and perform data analysis. You can also convert a multidimensional mosaic dataset to a .CRF file. To do so, use the Copy Raster tool, choose .CRF as the output format, and check the Process as multidimensional check box.
A number of raster data management tools support multidimensional rasters such as Resample, Clip, and Calculate Statistics. Additionally, you can project and transform your spatial data using the tools in the Projections and Transformations toolset, many of which support multidimensional rasters.
Visualizing multidimensional raster data
There are two ways to bring your multidimensional raster data into ArcGIS Pro: as a multidimensional raster layer and as a multidimensional mosaic dataset. To add the multidimensional raster layer, use the Add Data > Multidimensional Raster Layer option on the Map tab. Alternatively, you can use the Make Multidimensional Raster Layer tool to generate a layer from supported multidimensional data types.
By default, the system applies the Multidimensional Raster processing template and creates one multidimensional raster layer for each selected variable. The new raster layer contains the multidimensional information from the variable, which can be visualized, analyzed, and shared. You can also combine the selected variables into one multidimensional multivariate raster layer. Once in the map view, you can display the slices you want to see using the options in the Multidimensional Extent group on the Multidimensional tab.
You can also use the temporal profile chart to visualize and analyze your multidimensional raster data.
For more information on displaying a multidimensional raster layer, see Work with multidimensional raster layers.
For information on visualizing a multidimensional mosaic dataset, see Visualize a multidimensional mosaic dataset.
Analyzing multidimensional raster data
Complex time series analysis, height or depth trend analysis, forecasting, and regression are all possible with the ArcGIS Image Analyst extension in ArcGIS Pro. The tools available in the Multidimensional Analysis toolset allow you to aggregate your data over time, identify anomalies, explore trends, and detect change.
For more information, see Multidimensional Analysis in ArcGIS Pro.
Many multidimensional analysis tools are also available with the ArcGIS Spatial Analyst extension.