ArcGIS Image Dedicated enables organizations to manage, process, analyze, and share imagery and rasters at scale from data stored in AWS or Microsoft Azure cloud storage. Esri operates and automatically scales the dedicated cloud infrastructure, removing the burden of infrastructure management. Organizations can efficiently manage imagery, publish high-performance image services, generate analysis-ready products, and perform advanced analytics to turn imagery into actionable information.
This quarterly release introduces enhancements across Dynamic and Tiled imagery services, the ArcGIS Image Dedicated app, Pro Machines, Persist Imagery, and Log management capabilities. Key investments in this release focus on improving operational visibility, simplifying cloud storage administration, enhancing cost monitoring, and increasing the reliability of image processing workflows, helping administrators manage growing imagery environments with greater control and less operational effort.
What’s new?
- Credits usage dashboard for monitoring credit consumption and usage trends across deployments.
- Expanded Amazon S3 Access Point support for dynamic and tiled imagery servers and Pro Machines, which includes Allowed S3 Access Points configuration.
- Enhanced service details and service summary reports with additional usage, performance, and cost metrics.
- Email notifications for private storage connection operations in AWS and Microsoft Azure.
- View and copy Amazon S3 Access Point ARNs directly from the private storage connections page.
- Microsoft Azure SAS token support for secure log downloads.
- Improved persist imagery reliability, including extended queue retention and enhanced job recovery.
- Administration enhancements for Pro Machine which include last started time visibility and expanded storage access controls.
- Scene-Based Zonal Statistics workflow and geoprocessing capabilities for large-scale Sentinel-2 imagery analysis.
- Urban Heat Island Analysis tools for assessing surface heat patterns and heat risk.
Dynamic and Tiled Imagery Servers
This release introduces several enhancements to Imagery servers that improve visibility into service activity, simplify cloud storage administration, and provide greater control over how imagery services access data in AWS and Microsoft Azure environments.
Enhanced Service Reports
To help you better understand service performance and usage patterns, the Service Details and Service Summary reports under Admin > Reports > Dynamic Imagery Servers have been expanded with additional operational and cost-related metrics.
Service Details now include Total Services, Successful Requests, Failed Requests, Request Success Rate, and Total Cost.
Service Summary now includes Service Type, Service URL, Service Status, Successful and Failed Requests, Total Data Received, Total Cost, Service Duration, Minimum and Maximum Instance Counts, and Created By information.
These enhancements provide greater visibility into service utilization, request behavior, performance trends, and operational costs, helping you more effectively monitor and manage your imagery services.
Private Storage Connection Enhancements
Email Notifications for Storage Connection Operations
Email notifications have been added for private storage connection operations in AWS and Microsoft Azure. You’ll be automatically notified when storage connection operations are completed.
Validation for Storage Connection Names
Validation has been added to the storage connection creation workflow to prevent unsupported characters from being submitted. You now receive immediate feedback during data entry, helping avoid failed requests and improving the overall configuration experience.
Support for Amazon S3 Access Points
Imagery Servers running version 12.0 or later now support Amazon S3 Access Points when configuring data storage during server creation or when updating server properties. This enhancement enables credential-free access to Amazon S3 buckets for data access and log-writing operations when the appropriate bucket permissions are configured.
When deploying an Imagery server in AWS, you can also specify Allowed S3 Access Points to control which storage resources the server can access, supporting organizations that use an Access Point-based security model.
Note: S3 Access Points are not supported for processing and analysis services.
ArcGIS Server and Load Balancer log insights
As organizations collect larger volumes of operational data, efficient log storage and analysis become increasingly important. This release adds new capabilities that improve how you access, store, and analyze ArcGIS Server and Load Balancer logs.
Convert log data to GeoParquet
Log datasets can now be converted to GeoParquet format. You can use these files directly in ArcGIS Pro to perform spatial analysis, making it easier to explore and analyze patterns.
Download Logs Using Microsoft Azure SAS Tokens
Log management has been enhanced to support downloading logs from Microsoft Azure using Shared Access Signature (SAS) tokens. This provides a secure and streamlined method for accessing log files without requiring direct storage account credentials.
Persist Imagery
Several enhancements have been made to the persist imagery capability to improve operational reliability and make it easier to recover from interruptions during large-scale processing workflows.
Extended Queue Retention Period
The persist imagery queue retention period has been increased to five days, giving you additional time to review, manage, and recover queued jobs when necessary.
Improved Resume Job Experience
You now receive the appropriate resume job notifications when you submit jobs that earlier failed midway.
Better Handling of Missing Bundles
Persist imagery jobs now skip missing bundles that contain no raster data during CRF and cache generation, reducing unnecessary job failures when processing mosaic datasets with boundary that extend beyond the raster footprint. This enhancement prevents unnecessary job failures and improves the reliability of large-scale imagery processing workflows.
ArcGIS Image Dedicated App
The ArcGIS Image Dedicated app continues to evolve with improvements that simplify administration and provide better visibility into key deployment resources.
Improved Handling of Optional Parameters
The application now correctly handles missing optional parameters in API requests. Previously, pages could become unresponsive when optional values were omitted during the creation of data storage accounts, Pro Machines, or Imagery servers.
With this enhancement, null values returned by API requests are processed correctly, ensuring a more reliable user experience.
View and Copy S3 Access Point ARN
The private storage connections page now displays the Amazon S3 Access Point ARN associated with a storage connection. You can copy the ARN directly from the interface and use it when configuring bucket policies that control access through specific S3 Access Points.
PostgreSQL Flexible Server Resource ID
The RDBMS details page now displays the PostgreSQL Flexible Server Resource ID, making it easier for administrators to identify, reference, and manage the associated database resource.
Credits Usage Dashboard
Understanding resource consumption is an important part of managing imagery operations on a scale. To provide greater visibility into usage trends, a new credits usage dashboard has been added to the ArcGIS Image Dedicated app. The dashboard helps you monitor credit consumption across deployments, identify usage trends, and make more informed decisions about resource utilization.
Pro Machines
Beyond infrastructure and storage improvements, this release also expands the capabilities available within Pro Machine environments, making it easier to manage analysis resources and perform advanced imagery workflows.
View Last Started Time
Pro Machine details now include a Last Started Time field, allowing administrators to identify when a machine was most recently used. The timestamp is recorded when the machine is created and updated each time the Pro Machine is successfully started.
Allowed S3 Access Points
When creating Pro Machines in AWS, you can now specify Allowed S3 Access Points to control which approved S3 resources are accessible during analysis workflows. This enhancement supports organizations that use an Access Point-based storage management model while strengthening control over storage access.
Scene-Based Zonal Statistics Workflow Template
Organizations analyzing large volumes of satellite imagery can now take advantage of a new Scene-Based Zonal Statistics capability in ArcGIS Image Dedicated. Available through a geoprocessing endpoint and workflow template, it provides an end-to-end workflow for processing and analyzing large collections of Sentinel-2 imagery.
The workflow automates key processing tasks including scene discovery, cloud filtering and masking, spectral index generation, mosaic dataset creation, and zonal statistics computation for user-defined polygon features. Results can be exported in GeoParquet format to support downstream geospatial analytics workflows and integration with modern data platforms.
For organizations performing temporal analysis, the tool also supports optional Change Point Detection and Time Series Clustering through Space Time Cube generation, enabling deeper insights into spatial and temporal patterns across imagery collections.
By automating a traditionally complex, multi-step process, this enhancement helps you generate meaningful insights from large satellite imagery datasets more efficiently and with less manual effort.
Urban Heat Island Analysis Workflow Template
Organizations analyzing urban heat patterns can now leverage two new Urban Heat Island Analysis geoprocessing tools to assess relative surface heat and heat risk at complementary spatial scales. Using Land Surface Temperature (LST) derived from thermal remote-sensing imagery, such as Landsat, these tools streamline the identification of surface heat patterns and the assessment of relative heat risk across geographic regions.
The Relative Surface Heat Index (RSHI) tool quantifies pixel-level surface heat by comparing each pixel’s LST against that of a designated reference area. This enables users to identify relatively hotter and cooler locations, revealing the spatial distribution of surface heat across urban landscapes.
The Heat Risk Index (HRI) tool summarizes heat risk at the zone level by aggregating normalized heat-risk indicator scores within defined geographic areas, such as districts or administrative regions. The resulting scores support comparisons of relative heat risk across zones and help identify areas that may warrant further investigation.
By automating these calculations through geoprocessing workflows, the tools make urban heat analysis more efficient, consistent, and reproducible. Together, they enable organizations to move from pixel-level heat characterization to regional risk assessment, supporting data-driven urban planning and climate resilience initiatives.
Stay connected!
The October 2026 release continues to focus on the areas that matter most for managing imagery at scale: operational visibility, cloud storage security, cost awareness, and processing reliability. These enhancements help streamline administration and improve day-to-day operations across your ArcGIS Image Dedicated deployment.
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