Multidimensional data represents geophysical, environmental, climatological, or atmospheric phenomena that occur over space (two dimensional), time (another dimension), and/or height or depth (two more dimensions). These datasets can also contain multiple variables, such as precipitation, soil moisture, and temperature. Multidimensional raster data can be generated from satellite observations captured at different time intervals, or it can be generated from numerical models that aggregate, interpolate, or simulate data from other sources.
Datasets like these are extremely valuable for atmospheric, oceanographic, climate, and earth sciences. With multidimensional data, researchers can analyze changes through time, such as deforestation, and changes through space, such as changes in ocean salinity with depth. However, given the complex data structure, managing these datasets in order to analyze or visualize them quickly and effectively can be challenging. These datasets are also often very large, stored in a cloud environment, and frequently updated, introducing additional complications.
ArcGIS provides an intuitive experience to work with individual multidimensional datasets in their native format—netCDF, GRIB, and HDF. Collections of multidimensional datasets can be managed using mosaic datasets (the primary data model used in ArcGIS to manage imagery), or converted to CRF or transpose CRF to improve performance. Regardless which strategy you choose, you can then publish your data as a multidimensional image service to share with your organization or the public. Multidimensional data management tools and capabilities can be accessed through ArcGIS Pro or through ArcPy to automate processing.
Explore the following resources to learn more about managing multidimensional data in ArcGIS. (Not sure where to start? Look for the star by Esri's most helpful resources.)
Note:Multidimensional file formats (netCDF, GRIB, HDF) can be consumed using ArcGIS Pro Basic. To manage multidimensional data using mosaic datasets, you'll need ArcGIS Pro Advanced. To serve multidimensional mosaic datasets, you'll need ArcGIS Image Server.
Imagery Workflows resources
Community-supported tools and best practices for working with and automating imagery and remote sensing workflows:
- Consult a deep dive into best practices for managing and serving multidimensional data in ArcGIS Pro.*
Reference material for ArcGIS Pro, ArcGIS Online, and ArcGIS Enterprise:
- Read an overview explaining multidimensional raster data.
- Learn how to work with netCDF, GRIB, or HDF data directly in ArcGIS Pro as a multidimensional raster layer.
- Learn about the Multidimensional toolbox, including the tool for building a transpose CRF.
- Read how multidimensional data can be managed using a mosaic dataset and learn about the multidimensional raster types you can use to ingest the data.
- Get step-by-step instructions how to create a multidimensional mosaic dataset from netCDF files or from a set of time series images.
ArcGIS blogs, articles, story maps, and white papers
Supplemental guidance about concepts, software functionality, and workflows:
Esri-produced videos that clarify and demonstrate concepts, software functionality, and workflows:
- For users managing large collections of multidimensional data, watch a technical workshop about general best practices for managing imagery and rasters in the cloud (1 hr).
Resources and support for automating and customizing workflows:
Online places for the Esri community to connect, collaborate, and share experiences:
- See what the imagery community is saying about managing multidimensional data.
* Esri's top picks