Imagery and raster data contains invaluable information that can be used to identify patterns, find features, and understand change across landscapes. To extract useful information from imagery, you can process or analyze your data. For example, you may need to calculate a vegetation index to get an understanding of vegetation coverage from a multiband image, or you may want to find suitable locations to build solar power plants using statewide elevation and land cover raster data.
With the ArcGIS Enterprise portal, you can use built-in raster analysis tools to process and create persisted layers, which can be made available as imagery layers and feature layers. You can also process raster data with raster functions, and generate raster function chains and templates in the Raster Function Editor.
ArcGIS Image Server includes distributed raster analysis and distributed image processing. ArcGIS Image Server distributed analytics can work with a single large raster dataset, such as world elevation, or a high-resolution satellite image. It can also be applied to massive collections of imagery, such as the Landsat 8 or Sentinel-2 archives.
To learn more about accessing and running the tools, see Use the raster analysis tools. An overview of each raster analysis tool is below. The analysis tools are arranged in categories, which are logical groupings and do not affect how you access or use the tasks.
If you do not see the Analysis button or the Raster Analysis tab in Map Viewer Classic, contact your portal administrator. Your portal may not be configured with ArcGIS Image Server, or you may not have privileges to run the tools. If you do not have the permissions required for the tools, they will not be visible.
These tools allow you to use one dataset to define areas you want to summarize from the values of another dataset.
These tools allow you to explore spatial patterns in your data.
This tool creates a density map from point or line features by spreading known quantities of some phenomenon (represented as attributes of the points or lines) across the map. The result is a layer of areas classified from least dense to most dense.
This tool allows you to predict values at new locations based on measurements from a collection of points. The tool takes point data with values at each point and returns a raster of predicted values.
These tools allow you to perform analysis based on proximity and to find optimal paths to get to a destination.
This tool calculates Euclidean distance, direction, and allocation from a single source or set of sources.
Determine Optimum Travel Cost Network
This tool calculates the optimum cost network from a set of input regions.
The Optimal Region Connections tool provides enhanced functionality or performance.
Determine Travel Cost Path As Polyline
This tool calculates the least-cost polyline path between destinations and sources.
This tool calculates the accumulated distance for each cell to sources, allowing for straight-line distance, cost distance, true surface distance, and vertical and horizontal factors.
This tool calculates distance allocation for each cell to the provided sources based on straight-line distance, cost distance, true surface distance, and vertical and horizontal factors.
This tool calculates the optimal path from destinations to sources as a line.
This tool calculates the optimal path from destinations to sources as a raster.
This tool calculates the optimal connectivity network between two or more input regions.
These tools allow you to analyze multispectral imagery.
This tool performs an arithmetic operation on the bands of a multiband raster layer to reveal vegetation coverage information of the study area.
These tools calculate slope, aspect, and viewshed surfaces from digital elevation models (DEM).
This tool creates a surface that shows the slope of the input elevation data. Slope represents the rate of change of elevation for each digital elevation model (DEM) cell.
This tool identifies the areas that the input observer locations can see, accounting for surface topography. The input point locations can represent either observers (such as people on the ground or lookouts in a fire tower), or observed objects (such as wind turbines, water towers, vehicles, or other people). The results define the areas that can be seen from the observer locations.
This tool creates an aspect map from an elevation data source. Aspect identifies the downslope direction of the maximum rate of change in value from each cell to its neighbors. Aspect can be thought of as the slope direction. The values of the output raster will be the compass direction of the aspect.
This tool determines the contributing area above a set of cells in a raster.
These tools are used to manage image data, which includes clipping and masking, remapping pixel values, and converting to and from feature data.
This tool converts features to a raster dataset.
This tool converts a raster to a feature dataset as points, lines, or polygons.
This tool can clip a raster to a boundary, either to a rectangular area or to a shape you define interactively on the screen. You can clip to the extent of the area you currently have displayed on your map or by the study area defined by a polygon.
This tool allows you to change or reclassify the pixel values of the raster data. Pixel values are remapped by specifying a range of pixel values to map to an output pixel value. The output pixel value can be a valid value or a NoData value, which are pixels that do not have a known value associated with them.
This tool creates a table or a point feature class that shows the values of cells from a raster, or set of rasters, for defined locations. The locations are defined by raster cells, polygon features, polyline features, or by a set of points.
These tools allow you to detect specific features in an image or classify pixels in a raster dataset using deep learning inference tools.
Note:These deep learning service tasks, available at ArcGIS Enterprise 11.0, allow you to perform pixel classification, object detection, and object classification using existing deep learning models.
To perform deep learning workflows, Portal for ArcGIS and ArcGIS Server require additional configuration including the installation of deep learning Python modules. For details, see Configure ArcGIS Image Server for deep learning raster analytics.
This tool runs a trained deep learning model on an input raster and an optional feature class to produce a feature class or table in which each input object has an assigned class label.
This tool runs a trained deep learning model on an input raster to produce a classified raster, and each valid pixel has an assigned class label.
This tool runs a trained deep learning model on an input raster to produce a feature class containing the objects it finds. The features can be bounding boxes or polygons around the objects found, or points at the centers of the objects.
Note:At ArcGIS Enterprise 11.0, the Export Training Data For Deep Learning tool can only be used from ArcGIS API for Python and ArcGIS REST API. It is not available from Map Viewer Classic or ArcGIS Pro
These tools allow you to explore temporal patterns in time series imagery and raster data.
This tool generates a multidimensional raster dataset by combining existing multidimensional raster variables along a dimension.
This tool extracts the dimension value or band index at which a given statistic is attained for each pixel in a multidimensional or multiband raster.
This tool computes the anomaly for each slice in an existing multidimensional raster to generate a new multidimensional raster. An anomaly is the deviation of an observation from its standard or average value.
This tool estimates the trend for each pixel along a dimension for one or more variables in a multidimensional raster.
This tool computes a forecasted multidimensional raster using the output trend raster from the Generate Trend Raster tool.
In addition to raster analysis tools, you can use raster functions to perform complex image and raster processing workflows. You can use individual raster functions, or you can use the Raster Function Editor to combine multiple raster functions into processing chains, or raster function templates, using the visual programming tools. Raster function templates can be edited, saved, and shared with other members of your organization.
In the Map Viewer Classic, open the Raster Analysis pane and click the Raster Function Editor button to open the raster function editor window. The raster function editor contains a large gallery of raster functions.
To access a previously saved raster function template, or to use one of the built-in raster functions, click the Browse Raster Function Templates button in the Raster Analysis pane.
Access raster analysis tools and functions
There are several ways to access raster analysis tools and functions.
Access from Map Viewer Classic
If you have the required privileges to perform raster analysis, you can access the tools and functions from Map Viewer Classic.
To open the raster analysis tools, click Analysis, then click Raster Analysis.
To open the raster analysis functions, click Analysis, then click the Raster Analysis pane and click either the Browse Raster Function Templates button or the Raster Function Editor button .
Access from ArcGIS Pro
You can access raster analysis tools in ArcGIS Pro when signed in to your portal. See Raster analysis in Portal for details.
In addition to the raster analysis capabilities listed above, a number of imagery and raster geoprocessing tools and raster functions are available in ArcGIS Pro. For details, see Get started with image and raster processing.
Access from ArcGIS REST API
In addition to the user interface clients ArcGIS Pro and Map Viewer Classic, raster analysis services are also accessible through ArcGIS REST API.
Distributed raster analysis can be performed using a large suite of individual raster service tasks such as image services, raster analysis tasks, and ortho mapping tasks. The image processing tasks can be executed and results persisted by using the Generate Raster analysis task. This task uses a well-defined raster function JSON object as input and performs analysis based on the function definition. You can either directly use the system's built-in raster function supported by ArcGIS REST API or create your own custom raster models.
Developers can use raster function objects for distributed raster analysis processing and storage of distributed output.
Access from ArcGIS API for Python
ArcGIS API for Python allows you to query, visualize, analyze, and transform your spatial data using the raster analysis tools available in your organization. To learn more about the analysis capabilities of the API, see the ArcGIS API for Python documentation.
The raster analysis tools can be accessed through the arcgis.raster.analytics module. The raster analysis functions can be accessed through the arcgis.raster.functions module and the arcgis.raster.functions.gbl module modules. To work with raster function templates, use the arcgis.raster.functions.RFT module. The ortho mapping tasks can be accessed through the arcgis.raster.orthomapping module.