ArcGIS Image Server 10.8.1 includes updates, enhancements, and bug fixes.
If you're upgrading to ArcGIS Image Server 10.8.1, you must reauthorize your software. You can obtain a new license file from My Esri.
For updates in Image Server 10.8, see here.
New at 10.8.1
See what's new and improved in ArcGIS Image Server 10.8.1.
Create imagery content
- You can publish a raster processing template with an image layer. This allows you to browse and apply raster function templates to services that support it.
- Create a tile-only image service, known as a Tiled Imagery Layer.
- Inspect and edit image service configuration properties.
- Overwrite an image service that has been published to a stand-alone ArcGIS Server 10.6 or later site.
ArcGIS Ortho Maker
Enhancements to ArcGIS Ortho Maker include the following:
- Support for downloading products for offline use.
- Input GPS data into your projects from cloud stores.
Raster Analysis
Tools in Map Viewer
New raster tools are available for complex image processing and raster analysis.
Deep Learning toolset
Classify Objects Using Deep Learning—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.
Manage Data toolset
Sample—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.
Additionally, the Convert Raster to Feature tool in the Manage Data group has two new parameters, Create multipart features and Maximum vertices per polygon feature.
Multidimensional Analysis toolset
- Find Argument Statistics—Extracts the dimension value or band index in which the given statistic is attained for each pixel in a multidimensional or multiband raster.
- Generate Multidimensional Anomaly—Generates a multidimensional raster dataset by combining existing multidimensional raster variables along a dimension.
- Generate Trend Raster—Estimates the trend for each pixel along a dimension for one or more variables in a multidimensional raster.
- Predict Using Trend Raster—Computes a forecasted multidimensional raster using the output trend raster from the Generate Trend Raster tool.
Summarize Data toolset
The Summarize Raster Within tool has a parameter, Process as Multidimensional, to specify how the input rasters will be processed if they are multidimensional. The tools now also have an additional statistics type, Percentile, and a parameter, Percentile value, to specify percentile value to compute extreme events.
Raster Functions in Map Viewer
All raster functions in ArcGIS Pro 2.6 are now available from the Map Viewer.
Portal tools in ArcGIS Pro
When you are signed in from ArcGIS Pro to an ArcGIS Enterprise portal that has an ArcGIS Image Server configured for Raster Analysis, there are new tools and raster functions available, and additional capabilities have been added to some existing functions.
Manage Data toolset
The Convert Raster to Feature tool has two new parameters, Create Multipart Features and Maximum Vertices Per Polygon Feature.
Summarize Data toolset
- A new Zonal Statistics As Table tool has been added to calculate the values of a raster within the zones of another dataset and report the results to a table.
- The Summarize Raster Within tool and the Zonal Statistics raster function can process both multidimensional zone and value rasters. The tools and the function now also have an additional statistics type, Percentile, and a parameter, Percentile value, to specify percentile value to compute extreme events.
Use Proximity toolset
This toolset has been reorganized at this release, with some new tools added.
- The Distance Accumulation tool calculates accumulated distance for each cell to sources, allowing for straight-line distance, cost distance, true surface distance, as well as vertical and horizontal cost factors.
- The Distance Allocation tool calculates the distance allocation for each cell to the provided sources based on straight-line distance, cost distance, true surface distance, as well as vertical and horizontal cost factors.
- The Optimal Path As Line tool calculates the optimal path from a source to a destination as a line.
- The Optimal Path As Raster tool calculates the optimal path from a source to a destination as a raster.
- The Optimal Region Connections tool calculates the optimal connection of paths between two or more input regions.
The following tools were moved to the Use Proximity (Legacy) toolset: Calculate Distance, Calculate Travel Cost, Cost Path As Polyline, Determine Optimum Travel Cost Network, Determine Travel Cost Path As Polyline, and Determine Travel Cost Paths To Destinations.
Raster Functions in ArcGIS Pro
When you are signed in from ArcGIS Pro to an ArcGIS Enterprise portal that has an ArcGIS Image Server configured for Raster Analysis, there are new tools and raster functions available, and additional capabilities have been added to some existing functions.
New raster functions have been added:
- CCDC Analysis—Evaluates changes in pixel values over time using the Continuous Change Detection and Classification (CCDC) method and generates a multidimensional raster containing the model results.
- Compute Change—Enumerates the pixel changes that occur between two raster datasets. This function computes both absolute pixel value changes and categorical changes for thematic rasters. For categorical changes, it generates a layer depicting all areas that changed from one class to another.
- Detect Change Using Change Analysis Properties—Generates a raster containing pixel change information using the output change analysis raster from the Analyze Changes Using CCDC tool.
- Optimal Path As Raster—Calculates the optimal path from destinations to sources.
- Trend to RGB—Converts a trend raster from the Generate Trend function or the CCDC Analysis function into an RGB raster layer.
For existing functions, the following were updated:
- The Generate Trend function has five new parameters: Length of Cycle, Cycle Unit, RMSE, R-Squared, and P-Value of Slope Coefficient.
- The Linear Spectral Unmixing function supports multidimensional raster layers.
- The Multidimensional Filter function has a new parameter, Dimensionless.
- The Segment Mean Shift function has a new parameter for limiting the maximum allowed segment size.
- The Shaded Relief function has a new parameter, Hillshade Type.
- The Zonal Statistics function has a new statistics type, Percentile, and a new parameter, Percentile Value, to specify the percentile value.
The Distance raster functions have been reorganized under the Distance and Distance (Legacy) groups.
Raster Function and Objects in ArcGIS REST API
Six new raster function objects were added at 10.8.1:
- MultidimensionalRaster—Function adds a multidimensional dataset, such as netcdf, grib, hdf files, multidimensional mosaic dataset, or multidimensional CRF to a multidimensional raster.
- MultidimensionalRasterFilter—Function filters multidimensional raster along defined variables and dimensions.
- ProcessRasterCollection—Function processes each slice in a multidimensional raster or each item in a mosaic raster using different functions. This function can also aggregate multiple slices into a single slice.
- SpectralUnmixing—Function performs subpixel classification and calculates the fractional abundance of different land cover types for individual pixels.
- Trend—Function computes a forecasted multidimensional raster layer using the output trend raster from the Generate Trend function or Generate Trend Raster geoprocessing tool.
- TrendAnalysis—Function estimates the trend for each pixel along a dimension for one or more variables in a multidimensional raster.
Raster Analytics tasks in ArcGIS REST API
The following Raster Analytics tasks are new at 10.8.1:
- Analyze Change Using CCDC—Evaluates changes in pixel values over time using the CCDC algorithm, and generates a multidimensional raster containing the model results.
- Detect Change Using Change Analysis Raster—Generates a raster containing pixel change information using the output change analysis raster from the Analyze Changes Using CCDC tool.
- Distance Accumulation—Calculates straight-line distance or the least accumulative cost distance for each cell to the source over a cost surface, while optionally accounting for the surface distance and the horizontal and vertical factors.
- Distance Allocation—Calculates distance allocation for each cell to the provided sources based on straight-line distance, cost distance, true surface distance, as well as vertical and horizontal cost factors.
- Manage Multidimensional Raster—Edits a multidimensional raster by adding or deleting variables or dimensions.
- Optimal Path As Line—Calculates the optimal path from a source to a destination as a feature.
- Optimal Path As Raster—Calculates the optimal path from a source to a destination as a raster.
- Optimal Region Connections—Calculates the optimal connectivity network between two or more input regions.
- Publish Deep Learning Model—Publishes a model package of a deep learning model (.dlpk) containing the files and data required to run deep learning inferencing tools for object detection or image classification to your portal as a DLPK item.
- Zonal Statistics As Table—Summarizes the cells of a raster within the boundaries of zones defined by another dataset.
Additionally, existing Raster Analytics tasks are enhanced with new parameters, as listed below.
- Convert Raster to Feature
- The new createMultipartFeatures parameter specifies whether the output polygons will consist of single-part or multipart features.
- The new maxVerticesPerFeature parameter specifies the vertex limit used to subdivide a polygon into smaller polygons.
- Export Training Data For Deep Learning
- Now supports output to a fileshare data store path.
- The new referenceSystem parameter specifies the type of reference system to be used to export the image tiles.
- The new processAllRasterItems parameter specifies how raster items in an image service will be processed.
- The new blackenAroundFeature parameter specifies whether to blacken the pixels around each object or feature in each image tile.
- The new fixChipSize parameter specifies whether to crop the exported tiles such that they are all the same size.
- Generate Multidimensional Anomaly
- The calculationInterval parameter, which specifies the temporal interval that will be used to calculate the mean, now supports an EXTERNAL_RASTER option.
- The new referenceMeanRaster parameter specifies the reference raster dataset that contains a previously calculated mean for each pixel. The anomalies will be calculated in comparison to this mean.
- Generate Trend Raster
- The new trendLineType parameter specifies the type of line to be used to fit to the pixel values along a dimension.
- The new cycleLength parameter specifies the length of periodic variation to model.
- The new cycleUnit parameter specifies the time unit to be used for the length of a harmonic cycle.
- The new RMSE parameter specifies whether the root mean square error (RMSE) of the trend fit line will be calculated.
- The new R2 parameter specifies whether the R-squared goodness-of-fit statistic for the trend fit line will be calculated.
- The new slopePValue parameter specifies whether the p-value statistic for the slope coefficient of the trend line will be calculated.
- Summarize Raster Within
- The new processAsMultidimensional parameter specifies how the input rasters will be processed if the are multidimensional.
- A new option PERCENTILE was added to the statisticType parameter.
- The new percentileValue parameter specifies the percentile value to calculate.
- Train Deep Learning Model
- The outputName parameter provides an option to write the deep learning model package to a fileshare datastore location.
- The new backboneModel parameter supports several preconfigured neural network to be used as an architecture for training the new model. These include DENSENET121, DENSENET161, DENSENET169, DENSENET201, MOBILENET_V2, MASKRCNN50_FPN, RESNET18, RESNET34, RESNET50, RESNET101, RESNET152, VGG11, VGG11_BN, VGG13, VGG13_BN, VGG16, VGG16_BN, VGG19, VGG19_BN
- The new validationPercent parameter specifies the percentage (in %) of training sample data that will be used for validating the model.
- The new pretrainedModel parameter specifies the pretrained model to be used for fine tuning the new model. It is a deep learning model package (dlpk) portal item.
- The new stopTraining parameter secifies whether early stopping will be implemented.
- The new freezeModel parameter specifies whether to freeze the backbone layers in the pretrained model, so that the weights and biases in the backbone layers remain unchanged.
Raster Analytics in ArcGIS API for Python
arcgis.raster.analytics module
The following new functions have been added:
- analyze_changes_using_ccdc—Evaluates changes in pixel values over time using the CCDC algorithm, and generates a multidimensional raster containing the model results.
- detect_change_using_change_analysis_raster—Generates a raster containing pixel change information using the output change analysis raster from the arcgis.raster.analytics.analyze_changes_using_ccdc function.
- generate_trend_raster—Estimates the trend for each pixel along a dimension for a given variable in a multidimensional raster.
- linear_spectral_unmixing—Performs subpixel classification and calculates the fractional abundance of endmembers for individual pixels.
- manage_multidimensional_raster—Edits a multidimensional raster by adding or deleting variables or dimensions.
- sample—Creates a table that shows the values of cells from a raster, or set of rasters, for defined locations.
- optimal_path_as_line—Calculates the optimal path from a source to a destination as a feature.
- optimal_region_connections—Calculates the optimal connectivity network between two or more input regions.
- predict_using_trend_raster—Estimates the trend for each pixel along a dimension for a given variable in a multidimensional raster.
Additionally, the following functions have been enhanced:
- convert_raster_to_feature—Has two new parameters, create_multipart_features and max_vertices_per_feature.
- summarize_raster_within—Has a new statistics option of PERCENTILE, and a new parameter, percentile_value, to set the percentile value. Additionally, it also has another new parameter, process_as_multidimensional, to specify how the input rasters will be processed if they are multidimensional.
The following functions have been deprecated since ArcGIS API for Python version 1.8.1—determine_travel_costpath_as_polyline and optimum_travel_cost_network.
arcgis.raster.functions.gbl module
A new function, optimal_path_as_raster, to calculate, for each cell, its least-cost source based on the least accumulative cost over a cost surface, avoiding network distance distortion, has been added.
Additionally, the following functions have been enhanced:
- distance_accumulation and distance_allocation are enhanced to have multiple named outputs and can now take feature inputs.
- zonal_statistics—Has a new statistics option of PERCENTILE, and a new parameter, percentile_value to set the percentile value.
The following functions have been deprecated since ArcGIS API for Python version 1.8.1—calculate_distance, calculate_travel_cost, cost_backlink, cost_distance, cost_path, euclidean_allocation, euclidean_direction, euclidean_distance, path_distance, path_distance_allocation, and path_distance_back_link.
Image Services for ArcGIS REST API
New tools and tasks for image service tasks for ArcGIS REST API are listed below.
The Image Service resource supports the following operations at 10.8.1:
- Compute Cache Info—Computes and generates new image service tile cache schemes for image services.
- Compute Multidimensional Info—The operation is performed on an image service of a mosaic dataset. It is used for constructing a multidimensional info object based on its catalog table.
- Image Support Data—Returns image support data of the NITF based raster catalog item
- Slices—Returns the sliceId and multidimensional information for requested dimensional slices of the source dataset. It applies to image services of multidimensional datasets only.
- Statistics—Returns statistics of the image.
Additionally, existing raster analytics tools were enhanced with new parameters, as listed below.
- Export Image
- The new sliceId parameter is for image services of multidimensional datasets with raster tiles enabled on top. Each dimensional slice has its own image tile at a specific level, row, and column combination. The sliceId of a dimensional slice can be queried from image service slices resource.
- Histograms
- The new variable parameter can be used to request histograms for each variable in a multidimensional dataset.
- Image Tile
- The new sliceId parameter is for image services of multidimensional datasets with raster tiles enabled on top. Each dimensional slice has its own image tile at a specific level, row, and column combination. The sliceId of a dimensional slice can be queried from image service slices resource.
- Query (Image Service)
- The new rasterQuery parameter allows you to make a query based on key properties of each raster catalog item.
New at 10.8
See what's new in ArcGIS Image Server 10.8.
Create imagery content
Supports multidimensional data options to:
- Expose NetCDF/Grib/HDF raster types
- Create Image Collections (Mosaic Dataset)
Additional post-processing options on the Item page are available to:
- Build footprints
- Color correction
- Build seamlines
- Define NoData
- Build statistics
- Build overviews
ArcGIS Ortho Maker
Enhancements to ArcGIS Ortho Maker include the following:
- The ability to create a project with drone imagery in a registered data store
- Support RedEdge and Altum sensors
- Generate point clouds from cloud images
- GCP support vertical coordinate system
- Project sharing
- Global elevation raster data setup
Raster Analysis
Tools in Map Viewer
A new raster tool, Aggregate Multidimensional Raster is available in the Multidimensional Analysis toolset, to generate a multidimensional image service by aggregating existing multidimensional raster variables along a dimension.
Raster Functions in Map Viewer
146 raster functions are available for complex image processing and raster analysis. The raster functions can be combined into image processing chains using the Raster Function Editor window. Build your raster function template, test it, and apply it to your raster and mosaic datasets staged in your raster data store. The raster function chains, called raster function templates, can be saved and shared with members of your enterprise.
To create your custom raster function template, open your ArcGIS Enterprise Map Viewer, click the Analysis tab and choose Raster Analysis. The Raster Analysis pane will open and display categories of raster analysis operations. At the top of the Raster Analysis pane, click the Create a raster function template to perform complex processing and analysis button 
which opens Raster Function Template window. Drag and drop your raster functions displayed in the pane into the work space, double-click on the function in the editor to specify parameter settings. See Apply raster function templates to imagery in ArcGIS Enterprise portal for more details about how to build, apply and share raster function chains.
Raster Functions in ArcGIS Pro
When you are signed in from ArcGIS Pro to an ArcGIS Enterprise portal that has an ArcGIS Image Server configured for Raster Analysis, there are new tools and raster functions available, and additional capabilities have been added to some existing functions.
New raster functions have been added:
- Aggregate—Generates a reduced-resolution version of a raster on the fly and creates a dynamic raster output.
- Distance Accumulation—Calculates, for each cell, the least accumulative cost distance from or to the least-cost source, while accounting for surface distance along with horizontal and vertical cost factors.
- Distance Allocation—Calculates distance mapping for each cell to sources, allowing for true surface distance as well as vertical and horizontal cost factors.
- Random—Creates a dynamic raster on the fly with random cell values.
For existing functions, the following were updated:
- The Cell Statistics raster function can calculate single-band or multiband output based on the multiband processing type.
- The Least Cost Path function has been updated to use the Distance Accumulation function to perform distortion-free distance analysis.
- The Cost Path function has been updated with a new Force flow direction convention for backlink raster parameter.
- The Zonal Statistics function now have the Process as multidimensional parameter available, which allows you to calculate various statistics on each slice of a multidimensional value raster.
Raster Analytics tasks in ArcGIS REST API
The following Raster Analytics tasks are new:
- Find Argument Statistics—Extract the dimension value or band index at which a given statistic is attained for each pixel in a multidimensional or multiband raster.
- Compute Color Correction—Computes color corrections for the mosaic dataset, usually after the mosaic has been block adjusted.
- Compute Seamlines—Compute seamlines between overlapping images comprising an image collection, usually after the image collection is block adjusted.
- Linear Spectral Unmixing—Performs subpixel classification and calculates the fractional abundance of end members for individual pixels.
- Classify Objects Using Deep Learning—Classify objects based on overlaid imagery data using the designated deep learning model and generate a feature service with new assigned label for each object.
- Train Deep Learning Model—Train a deep learning model using the output from the Export Training Data for Deep Learning tool.
Support is available for input raster from data store, and raster analysis service for single node multiple GPU parallel processing for Deep Learning.
Raster Analytics in ArcGIS API for Python
arcgis.raster.analytics module
The following new functions have been added:
- aggregate_multidimensional_raster—Generates a multidimensional image service by aggregating existing multidimensional raster variables along a dimension.
- build_multidimensional_transpose—Transposes a multidimensional raster dataset, which chunks the multidimensional data along each dimension to optimize performance when accessing pixel values across all slices.
- find_argument_statistics—Extracts the dimension value at which a given statistic is attained for each pixel in a multidimensional raster.
- generate_multidimensional_anomaly—Computes the anomaly for each slice in a multidimensional raster to generate a multidimensional dataset.
- generate_trend_raster—Estimates the trend for each pixel along a dimension for a given variable in a multidimensional raster.
- predict_using_trend_raster—Compute a forecasted multidimensional raster using the output trend raster from the generate_trend_raster function.
- subset_multidimensional_raster—Subsets a multidimensional raster by slicing data along defined variables and dimensions.
arcgis.raster.functions module
The following new functions have been added:
- constant_raster— Creates a virtual raster with a single pixel value.
- random_raster—Creates a dynamic raster on the fly with random cell values.
Additionally, the following functions have been enhanced:majority, max, mean, med, min, cellstats_range, std, sum, variety to calculate single-band or multiband output based on the multiband processing type.
arcgis.raster.functions.gbl module
The following new functions have been added:
- distance_accumulation—Calculates, for each cell, the least accumulative cost distance from or to the least-cost source, while accounting for surface distance along with horizontal and vertical cost factors.
- distance_allocation—Calculates distance mapping for each cell to sources, allowing for true surface distance as well as vertical and horizontal cost factors.
- euclidean_back_direction—Calculates, for each cell, the direction, in degrees, to the neighboring cell along the shortest path back to the closest source while avoiding barriers.
- expand—Expands specified zones of a raster by a specified number of cells.
- flow_length—Creates a raster layer of upstream or downstream distance, or weighted distance, along the flow path for each cell.
- shrink—Shrinks the selected zones by a specified number of cells by replacing them with the value of the cell that is most frequent in its neighborhood.
- sink—Creates a raster layer identifying all sinks or areas of internal drainage.
- snap_pour_point—Snaps pour points to the cell of highest flow accumulation within a specified distance.
- stream_order—Assigns unique values to sections of a raster linear network between intersections.
Additionally, the following functions have been enhanced: euclidean_allocation, euclidean_distance, euclidean_direction, flow_distance, cost_path, zonal_statistics.