ArcGIS enables you to work with a wide variety of
imagery acquired from different sources. These image management
workflows provide best practices for managing large collections of
imagery to make the imagery quickly and efficiently accessible. The
image management workflows are described in the Image Management Guidebook which begins with a general overview of all aspects related to image management, followed by workflow-specific sections regarding best practices for all workflows listed below.
The following additional components unique to each workflow are referenced below:
- Scripts and associated documentation for the automation of workflows.
- Sample data to be used with the scripts to create sample mosaic datasets and image services.
- See this Group on ArcGIS Online for workflow-specific example scripts and data, as well as the underlying Mosaic Dataset Configuration Script (MDCS) which is used for all workflows.
- Links to live example services on ArcGIS Online.
- Links to other resources such as Forums, Blogs, and Help system.
Following are the workflows that are currently being documented. If you have questions, please do check out the corresponding FAQs and post questions (and answers) to Forums, and alternatively let our team know by sending email to ImageManagementWorkflows@esri.com.
Preprocessed Orthophoto Imagery
Preprocessed orthophoto imagery generally exists as sets of processed tiled images, either 3-band color or color infrared imagery, with more recent collections including 4 spectral bands (RGB + Near IR). The "preprocessed" name implies the imagery is ready to use (orthorectified and typically color corrected) without further processing, but workflows are still required for managing and sharing the data with end users. Organizations faced with managing this data often have multiple image collections, with different resolutions and multiple dates, which may also be stored in different projections and data formats. This workflow discusses the different formats that are most typical, and provides examples for managing multi-year collections, in two different modes (i.e. "Always show most recent data on top" as well as "Use time slider to select imagery by year").Quick Links
- For more information on the image management workflow for Preprocessed Orthophotos, please refer to the Image Management Guidebook.
- ArcGIS Online Group
- Visit the ArcGIS Image Management Workflows AGOL group where you will find downloadable sample data and user-modifiable python geoprocessing tools for managing and sharing Preprocessed Orthophotos.
- See here for an open discussion with other users regarding the workflow for managing and sharing Preprocessed Orthophotos.
Multispectral Satellite Imagery
This workflow addresses management of imagery from medium (5-30m) and low resolution (>30m) satellites, such as RapidEye, SPOT, Landsat & ASTER. This imagery is commonly used for regional or country-wide assessment and monitoring. Typical applications include agricultural or environmental monitoring. A significant value of images from these satellites are multispectral that support a wide range of applications, which rely on analysis utilizing the different spectral bands. Aspects such as atmospheric correction are of higher importance. By following this workflow, the image services generated for this type of datasets can be used for fast visualization and analysis.Quick Links
- For more information on the general image management workflows, please refer to the Image Management Guidebook. A chapter in this guidebook specific to Multispectral Satellite Imagery will be published soon.
- Frequently Asked Questions for Image Management workflows - Multispectral Satellite Imagery
- ArcGIS Online Group
- Visit the ArcGIS Image Management Workflows AGOL group where you will find downloadable sample data and user-modifiable python geoprocessing tools for managing imagery from Landsat 8. Additional examples for data from other satellites will be added in the future.
- See here for discussion regarding the workflow for managing Multispectral Satellite Imagery.
This workflow describes organization and sharing of elevation data from different sources in multiple resolutions, and will need to be maintained over time as new data (e.g. from Lidar) is acquired. Derived visualizations such as hillshades may be generated on the fly.
Elevation or terrain data is used for many applications—in some cases to directly extract information, such as computing viewsheds, contours and profiles—and also for visualizing topography and as input for other processes, such as orthorectification. Organizations often obtain publically available elevation data and then supplement it with datasets procured off-the-shelf or custom datasets collected for the organization via contract.
- Example web application and live services
- Within ArcGIS Online, Esri is hosting a worldwide elevation service (with related services generated on-the-fly) that was created using the automated workflows. Please see this group in ArcGIS Online for information on those live image services. In addition, this web application accesses the live image services, providing an example Silverlight application built using Esri's web APIs.
To access the live services, you need to log in with an ArcGIS Online Subscription account.
- For more information on the elevation workflow, please refer to the Image Management Guidebook.
- Frequently Asked Questions - Image Management Workflows for Elevation
- ArcGIS Online Group
- Visit the ArcGIS Image Management Workflows AGOL group where you will find downloadable sample data and user-modifiable Python scripts, which can be executed in ModelBuilder or via command line batch files.
- See here for discussion regarding the workflow for managing Elevation data.
The workflows for the following imagery types will be released soon:
- Orthophoto Imagery—Orthophoto imagery generally exists as sets of processed tiled images, often with different resolutions and multiple dates, in different projections and formats. Imagery may be a mixture of older panchromatic imagery, 3-band color or color infrared imagery, and newer 4 band multi-spectral imagery.
- High Resolution Satellite Imagery—This workflow is for imagery from high resolution satellites (<5m) such as Ikonos, GeoEye, QuickBird, Worldview, Pleiades,etc. This data
is typically multispectral, resulting in different band combinations,
such as pan-sharpening, RGB, false color IR, and NDVI. The data may
be rectified, or may require georeferencing using a rational
polynomial coefficient (RPC) based sensor model.
The multispectral aspect of the imagery is important and users often utilize the additional bands to extract information.
- Aerial Frame Imagery—This workflow is for imagery from frame-based digital camera systems flown on small aircraft or unmanned drones, including sensors such as the Vexcel UltraCam, Intergraph DMC, Trimble DSS, DiMAC, VisionMap A3, and others. Each image is typically processed into a simple format such as TIF or JPEG. Metadata is generally stored in a tabular format along with sensor calibration information. Some of these sensors have a higher resolution panchromatic image and need to include pan sharpening as a standard process. This workflow is intended to quickly catalog the imagery and make it accessible, refine the processing to orthorectify the imagery more accurately, then color balance and mosaic the imagery for better interpretation.
- Oblique Imagery—This workflow is for imagery from specialized oblique aerial systems as well as nadir-viewing sensors with very wide field of view, to manage and exploit the information from the oblique angles. There is an increasing trend to capture oblique imagery from airborne sensors to enable visualization and mensuration of the sides of objects such as buildings. Such imagery is captured by a range of camera systems from Pictometry, Trimble, Microsoft, Leica, Midas and VisionMap.
- Historical Imagery—This workflow is for large archives of historical aerial imagery, often spanning many decades, and takes into account aspects such as the varied metadata and imprecise image location, often extracted from hardcopy photo indices. These images have significant value for change monitoring when they become accessible and are georeferenced for comparison to newer imagery.
- Scientific Data—This workflow is for imagery from multispectral science-mission satellites with multitemporal and multispectral data, often obtained in a range of more complex formats such as HDF. Imagery from multispectral science-mission satellites is commonly used for monitoring applications such as weather and more science and research applications.
- Thematic Data—This workflow is for raster data files representing classified imagery or similar thematic maps, emphasizing the attributes of the various classes. These collections of thematic map raster datasets are often very large, and need to be organized, managed and made accessible to large user groups.