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Keeping maps current requires a complete view of our changing world. Maxar and Bee Maps, powered by Hivemapper, have tested a three-layer approach that combines satellite change detection, crowdsourced street-level imagery and high-resolution satellite imaging to create the most comprehensive mapping solution available.

This combination provides unmatched capability: Maxar's proprietary algorithm identifies where changes have occurred, Hivemapper contributors capture detailed ground-level views, and high-resolution satellite imagery from Maxar provides the contextual overhead perspective that connects everything together. Early results from Austin show 80% success in documenting identified changes.

Customers of Maxar and/or Bee Maps can deploy this innovative approach into their respective workflows for timely and precise map updates today.

The Challenge

Maps become obsolete quickly. For centuries, mapmakers have used manual surveys and local authority reports to trigger an update in their basemaps. These surveys and reports can take months, sometimes even years, to produce—and might be outdated by the time they’re published, especially in metro areas with rapidly changing infrastructure.

Even modernized secondary signals like in-app driver alerts and on-board sensor data leave mapmakers with unverified changes. Voluntary in-app reporting could easily confuse temporary changes (a detour) for permanent ones (a new highway). On-board sensor data only detects a new road once it’s accessible to the public. These signals might be closer to real-time indicators—but still lead to false positives or unnecessary map updates.

The Three-Layer Solution

Maxar and Bee Maps have devised a data-backed joint solution to outpace manual surveys and overcome limitations of unreliable secondary signals. First, Maxar applies proprietary change detection algorithms across broad areas to spot where changes have occurred. Once these localized areas are identified, Hivemapper's street-level images confirm these changes up close. Finally, Maxar tasks an imagery collection of the current area to replace the outdated view. This approach helps mapmakers work faster and more accurately by showing exactly what has changed and where, eliminating guesswork and wasted effort.

1. Maxar's Change Detection: Finding What's New

Maxar's change detection technology systematically monitors entire regions to identify locations where changes have occurred:

• Automated detection of new construction and infrastructure changes
• Broad area coverage without requiring ground presence
• Monthly change monitoring
• Integration into customer mapping workflows

2. Bee Maps Street View: Ground Truth Verification

Bee Maps generates and processes fresh street-level imagery from Hivemapper's network of drivers, which has mapped 33% of the global road network through crowdsourced data collection:

• Targeted bounties called "bursts" incentivize drivers to document change locations
• Rapid response with 11.81% of locations covered within 7 days in the Austin pilot
• Granular detail into road networks and specific features like speed limits

3. Maxar's High-Resolution Imagery: The Complete Picture

High-resolution satellite imagery provides the crucial overhead context:

• Detailed views that connect street-level observations to the broader landscape
• Visibility into areas that may be inaccessible from the street
• Temporal comparisons showing before-and-after states
• Overhead views of buildings and neighborhoods enabling accurate digitization

Austin Pilot: Proving the Concept

To test this innovative approach to integrated mapping, Maxar and Bee Maps chose Austin, Texas as a testing ground. 

Austin, one of the fastest growing metropolitan areas in the United States with more than 10,000 new homes built annually, is a particularly challenging place to keep maps up to date. New developments often require changes to roadway infrastructure, so surveying the roads every few years is not enough to maintain accurate maps.

The pilot began with Maxar’s Building and Road Change product, which offers building and road change monitoring around the world. Change vectors in the Austin metropolitan area indicated locations where changes were identified during the 6-month change detection timeframe.

Maxar provided Bee Maps a dataset of the changes it detected. Bee Maps proceeded to activate incentives called “bursts" for these specific coordinates, encouraging Hivemapper drivers to visit and capture fresh street-level imagery.

There were two key questions to answer:

1. What share of the time would the Hivemapper Network be able to get a street-level view of an area where a change had been detected?
2. On average, how long would it take to get a street-level view?

On both fronts, the results exceeded expectations.

1. 80% of the time, Bee Maps was able to validate the change detected from satellite imagery using crowdsourced street-level data collection.
2. 65% of the time, the street-level data used to validate the satellite detections was less than 180 days old – and 29% of the time, it was less than 30 days old.

The combination of satellite and street-level imagery was particularly powerful for documenting new housing developments. In some cases, entire neighborhoods had been built since the previous satellite imagery was captured. 

When a new neighborhood is built, satellite imagery offers an ideal view for establishing the footprint of new buildings and road infrastructure. Street-level map data adds crucial details about road signage, speed limits and intersection configurations that cannot be confirmed from satellite imagery alone. 

Some mapmakers source imagery from multiple vendors to manage a similar process in-house. This pilot validated for Maxar and Bee Maps that an integrated change detection process across the leading providers of satellite and street-level imagery could dramatically expedite the process of keeping maps up to date.

While the pilot achieved impressive coverage, we also identified areas for improvement. 

In 20% of cases where we detected a change using satellite imagery, it was challenging to document the change from street level – usually because the changes occurred too far from publicly accessible roads. 

This finding reinforced the value of the three-layer approach, as Maxar's high-resolution satellite imagery could still provide documentation of these hard-to-reach areas.

Commercial Applications

Leading map platforms need navigation systems with dependable, up-to-date routing information. By focusing resources specifically on verified change areas in the road network, they eliminate the inefficiency of scheduled regional updates or unreliable user reports.

But large-scale mapmakers aren’t the only sector that depend on map data that reflects real-world conditions,

Government agencies apply this information to monitor development compliance, track infrastructure changes and coordinate services efficiently. Emergency response teams depend on current road access data, particularly in rapidly developing areas or following natural disasters where traditional map updates lag behind actual conditions.

Transportation and logistics organizations utilize mapping intelligence to improve operations. Rideshare platforms identify when construction has modified pickup points, optimizing driver-passenger connections. Delivery services receive timely alerts about building entrance changes, reducing failed deliveries. Freight logistics companies access advance notifications about loading dock modifications, enabling precise route planning and minimizing delays.

For supply chain management, the solution ensures that warehouse locations, distribution centers and delivery routes remain accurately mapped as facilities expand or relocate. The retail sector leverages this comprehensive mapping approach for site selection, using the complete picture to understand new development areas from both the broad neighborhood context and specific street-level accessibility, while insurance companies employ the multi-angle documentation to assess property changes and update risk models with greater precision.

Get started today

Maxar and Hivemapper are both leaders in their respective industries—satellite imagery and street-level mapping. Together these two companies have proven that combining their capabilities delivers mapping insights that no single technology could achieve alone. 

Whether you’re already working with Maxar's Earth Intelligence solutions, leveraging Hivemapper's street-level data, or exploring these capabilities for the first time, both companies are ready to integrate their proven technologies into your mapping workflow to deliver the comprehensive coverage your applications demand.