High resolution satellite imagery is typically better than 5-meter resolution, gathered by satellites such as Worldview, Pleiades, Deimos 1, Ikonos, GeoEye, and QuickBird (among others). It is usually multispectral, often including red, green, blue, and infrared bands (RGB-IR), and sometimes a panchromatic band. Vendors deliver high-resolution imagery as a variety of products with different processing levels. These products may have limited processing, or have some combination of radiometric correction, georeferencing, or orthorectification applied. They may also include various forms of metadata.
Organizations often manage large collections of high-resolution satellite imagery and accompanying metadata, often including overlapping images gathered on multiple dates. This data generally needs additional processing before it is helpful for end users. Users may also wish to visualize the data in different ways—looking at only the newest imagery, for example, or filtering out low-quality images. Additionally, since the imagery is multispectral, users may wish to view different band combinations, indexes, or pansharpened imagery.
ArcGIS Desktop includes the tools necessary for any preprocessing your imagery requires, including geolocation, radiometric correction, georeferencing, and orthorectification. Managing your imagery using a mosaic dataset configured for a specific type of high-resolution satellite imagery then makes it straighforward to visualize, query, and analyze your data. The mosaic dataset is the recommended data model for managing, accessing, processing, and visualizing imagery in ArcGIS. With a mosaic dataset, you can organize metadata, define mosaicking rules, and include raster function templates for different visualizations of spectral data (like NDVI or color infrared). Beyond direct use in ArcGIS Pro, they are also optimized to share imagery with end users and applications. High-resolution satellite imagery managed with mosaic datasets can be shared two ways:
- It can be shared as a three-band, 8-bit raster
tile cache (like Esri basemaps). The tile cache can be created in ArcGIS Pro, then uploaded to ArcGIS Online for hosting and sharing.
Note:Esri's World Imagery basemap features satellite imagery for the world and high-resolution aerial imagery for many areas. For some applications, this may be a satisfactory alternative to managing your own collection of high-resolution imagery.
- If end users will need dynamic access to the imagery (if you want to take advantage of raster functions to include color infrared, natural color, and NDVI views, for example, or control the display order of the imagery), the imagery can be shared as an image service using ArcGIS Image Server.
Explore the following resources to learn more about managing high-resolution satellite imagery. (Not sure where to start? Look for the star by Esri's most helpful resources.)
Note:To create and edit mosaic datasets, you need ArcGIS Desktop Standard or Desktop Advanced. If you plan to perform bundle block adjustment or create digital terrain models, you'll need the ortho mapping capability of ArcGIS Pro Advanced. To serve mosaic datasets as dynamic image services, you need ArcGIS Image Server. To host raster tile cache, you can use ArcGIS Online or ArcGIS Server.
Imagery Workflows resources
Community-supported tools and best practices for working with imagery and automating workflows:
- Download sample Python scripts for managing high-resolution satellite data using best practices. *
- Read detailed documentation explaining best practices for creating mosaic datasets and structuring and formatting imagery and rasters.
Reference material for ArcGIS Pro, ArcGIS Online, and ArcGIS Enterprise:
- Learn more about using mosaic datasets to manage imagery in ArcGIS Pro.
- Consult a list of supported satellite sensor raster types.
- Learn about orthorectifying your imagery in ArcGIS Pro.
- Find more information about using raster functions to visualize your imagery in ArcGIS Pro, especially functions for Pansharpening, NDVI, NDVI Colorized, Extract Band, and Composite Band.
Authoritative learning resources focusing on key ArcGIS skills:
- Watch Managing Raster Data Using ArcGIS (2-hr web course) to learn how to use mosaic datasets to enable efficient data storage and fast visual performance. *
Resources and support for automating and customizing workflows:
- Visit the MDCS GitHub repo to download a Python script to help automate the creation and configuration of mosaic datasets.
- If you plan to manage your satellite imagery in the cloud, or want to optimize the data format for faster access, visit the OptimizeRasters GitHub repo for scripts and tools to optimize data transfer and management.
Online places for the Esri community to connect, collaborate, and share experiences:
- Discuss this workflow with the imagery community.
* Esri's top picks