Skip To Content
ArcGIS Developer

Get started with the Raster Analysis service

The Raster Analysis service contains a number of tasks that allow you to perform common raster-based spatial analyses on your data.

These tasks are also available as tools in the portal Map Viewer Classic. These tools allow portal members to perform raster analysis against layers they have access to. To learn more about accessing these tasks using Map Viewer Classic, see Perform raster analysis in the Portal for ArcGIS Help. In some cases, the Raster Analysis REST API has functionality that is not exposed in the portal Map Viewer Classic.

To access the Raster Analysis service using JavaScript, see the JavaScript API topic Working with Analysis Widgets.

Starting with the ArcGIS Enterprise 11.1 release, a number of deep learning raster analysis services are introduced. These deep learning service tasks allow you to export training samples from imagery and perform image feature identification to classify pixels and detect features using existing deep learning models.

In order to perform these deep learning workflows, Portal for ArcGIS and ArcGIS Server require additional configuration to install deep learning python modules. Please refer to Configure and deploy ArcGIS Enterprise for deep learning raster analytics for more details.


The administrator of your organization needs to configure Portal for ArcGIS so that the Raster Analysis server capability is enabled. To use the analysis tasks, the administrator needs to grant you privileges to Create, update, and delete content and Publish hosted features. To use Raster Analysis tasks, you also need Publisher privileges.

Common patterns

The tasks in the Raster Analysis service all share a common pattern described as follows:

  • For most tasks, one or more of the input parameters are rasters. These rasters can come from an image service, map service, or in the form of a raster dataset. See Raster Input for more information.
  • As described in Raster Output, all raster analysis tasks create new data. How data is returned to you is controlled by the outputName parameter.
  • All tasks have a context parameter, which controls certain aspects of task execution.
  • All tasks execute asynchronously. That is, when you submit a request, a job identifier is returned to you, which you can use to track progress and retrieve results. See Checking job status for more information.

Related topics

In this topic
  1. Licensing
  2. Common patterns