Satellite imagery
Mapbox Satellite is a global basemap of high resolution satellite and aerial imagery. The Mapbox Satellite Streets style combines the Mapbox Satellite basemap with vector data from Mapbox Streets to bring contextual information to your map.
This guide will introduce Mapbox imagery resources and explain how you can upload your own imagery to use with Mapbox tools.
To learn more about Mapbox imagery, including data sources and data coverage, read our Mapbox imagery guide.
Key terms
It can be helpful to understand key terms related to imagery.
For more detailed definitions, click the terms below or visit the Glossary.
- aerial imagery: visual raster data acquired by an instrument on a plane, drone, or other aerial source
- satellite imagery: visual raster data acquired by a spaceborne instrument
- raster: a pixel-based data format that stores data in a grid structure
- tileset: a collection of raster or vector data broken up into a grid
Clockwise from top left: MODIS, Landsat, Maxar satellite, Vexcel aerial.
Use Mapbox imagery
You can use Mapbox imagery data in the following Mapbox-owned styles or tilesets, available to anyone using a valid Mapbox access token.
Imagery styles
Click a style name below to learn more about the style in our Styles API documentation:
Learn more about using styles in our Map Design getting started guide.
Imagery tilesets
Click a tileset name to learn about its layers, data sources, and more:
Learn more about using tilesets in our Mapbox imagery tileset guide.
Upload your own imagery
If you want to use your own imagery with Mapbox, see our documentation for our Mapbox Tiling Service, Mapbox Studio, and Uploads API. Make sure you convert your imagery into GeoTIFF format before you upload.
Once you have uploaded your data, it will be automatically converted into a custom raster tileset which you can then add to your Mapbox project.
To learn more what you can do with tilesets, see these guides:
- To add a tileset to a web map, see our Add a video example.
Imagery use cases
When looking to understand our thousands of customers and millions of users, we focus on the broader application of imagery and how to categorize the use case, be it business, scientific, humanitarian, and government or something else. Our users break down into categories by context:
- A wide-view user — Customers who visualize global/country datasets
- An outdoor user — Rural (recreation, non-precision agriculture), non-urban business intelligence, visualization/simulation
- A basemap user — Most app developers, real estate, business intelligence, fleet and logistics management, navigation
Sampling of typical industry vertical markets and their respective imagery needs
Samnakdong, South Korea © Maxar 2020.
Drilling down on customer usage
Over the past few years, we have been improving our approach to update our imagery basemap based on using anonymized telemetry to identify where people are looking at our maps, and systematically assessing imagery quality at scale.
We combine this with an assessment of aggregated data from our largest satellite users to get a deeper understanding. Looking at the data in the chart below, we see the vast majority of views across our top 100 customers come from zoom levels 17+, or imagery greater than 1-meter resolution (peaks on the right of the charts).
Distribution of zoom level requests for the top 100 mapbox.satellite users.
This approach lets us segment our customers based on their usage patterns. With this information, we can make data-driven decisions on our imagery allocation and forecast which updates will help which customers will find use from an update.
Bay Bridge Toll Plaza, Oakland, CA © Vexcel Data 2022
As a result of these analyses, we are focusing the majority of our attention on higher resolution data sets. We now have high-resolution aerial imagery in the contiguous US, covering about 80% of the country’s population. As we move forward, we are continually working with our imagery partners to keep the highest demand areas up-to-date with high resolution, high-quality imagery.
Data updates
We update the 4 petabyte (PB — or 4 M gigabytes) global imagery layer used for our Mapbox Satellite data from nearly a dozen sources.
Any single image offers a view of a place at a moment in time that can be used to find new development sites, aid in disaster response, serve as a source of ground truth, and track changes.
How do we determine where to update?
To determine where to update imagery, we take into account industry use cases and needs, customer feedback, and internal data on tile requests and zoom levels.
We optimize our basemap for a balance of recency and aesthetic quality depending on data availability as well as analyzing customer usage to prioritize global imagery updates.
Where do we source our data?
Our satellite data consists of imagery sourced from multiple satellites and airplanes, from both commercial and open sources. View our list of sources on our data sources page.
What is the breakdown of imagery by zoom level?
Imagery sources and resolutions are tied to specific zoom levels to provide consistency and quality of data.
These zoom levels break down as follows:
- Zoom levels 0-8 use de-clouded data from NASA MODIS satellites.
- Zoom levels 9-12 use primarily Maxar satellite imagery and NASA/USGS Landsat 5 through 9 imagery in limited locations.
- Zoom levels 13-16 use Maxar's Vivid product for the majority of global coverage.
- Zoom levels 16+ use Vexcel aerial imagery over North American - and some European - cities, and open aerial imagery from the Netherlands, Denmark, France, Germany, Chechia, Poland, Spain, New Zealand, and other regions. image
Clockwise from top left: MODIS, Landsat, Maxar satellite, Vexcel aerial.
How do we quality control our data?
All our imagery is checked for color fidelity, optimized, and composited together into a single raster tileset by our Satellite team. The end result is an imagery layer that provides varying levels of detail based on the needs of users looking at larger, less detailed areas or smaller, more detailed areas.
Port of Long Beach, Los Angeles, CA © Vexcel Data, 2022