As transportation planning and modeling continue to evolve, so does the data that underpins analysis. Two commonly confused sources of mobility insight are cell carrier data and location-based services (LBS) data. While both are derived from mobile devices, they differ significantly in how they are collected, the level of detail they provide, and—most importantly—their usefulness for transportation applications.
Understanding these differences is critical for planners, modelers, and researchers who rely on accurate, defensible, and actionable mobility data.
Cell carrier data is derived from wireless network signaling between mobile devices and cellular towers. Device locations are inferred based on which tower—or group of towers—a device connects to at a given time.
Very large sample sizes
Long history of use in mobility analysis
Useful for identifying broad, regional movement trends
Spatial resolution is limited by cell tower density
Location accuracy can vary widely, particularly in rural areas
Temporal resolution depends on network events rather than continuous movement
When a device is out of network range, no location information is captured
Less reliable for precise trip origins, destinations, and routes
Because of these limitations, cell carrier data is generally best suited for high-level trend analysis rather than detailed transportation planning or modeling.
LBS data is generated by smartphone applications that collect GPS-based location information, with user consent. These observations are typically far more frequent and precise than those derived from cellular networks.
Importantly, LBS data does not rely on continuous cellular network connectivity. Even when a device travels through areas with poor or no carrier coverage, GPS can still record location—resulting in more complete and continuous trip information.
Much higher spatial granularity, often accurate to within a few meters
Strong temporal resolution, enabling trip-level analysis
Captures movement even when devices are out of cellular network range
Better identification of true trip origins and destinations
Improved ability to distinguish travel modes and trip purposes
Well-suited for corridor studies, O-D matrices, and behavioral analysis
Sample sizes may be smaller than carrier data (though still robust)
Requires careful processing and validation to ensure representativeness
For most modern transportation applications, granularity and continuity matter—and this is where LBS data clearly excels. Compared to cell carrier data, LBS data enables planners and modelers to:
Build more accurate origin–destination matrices
Analyze time-of-day and day-of-week travel behavior
Support transit, active transportation, and multimodal studies
Improve model calibration and validation
Conduct sub-area, corridor, and site-level analyses
Better understand trip frequency, chaining, and purpose
Link travel behavior with land use and demographic context
In short, LBS data aligns more closely with how transportation systems actually operate and how planners need to evaluate them.
AirSage’s roots are in cell carrier data. However, as transportation planning and modeling needs evolved, AirSage made a strategic shift in 2017 to location-based services data and has since built an extensive LBS database supporting multi-year analysis.
Today, AirSage brings deep expertise in sourcing, processing, validating, and applying LBS data for transportation planning and modeling. Rigorous methodologies and ongoing quality checks ensure that the data is accurate, reliable, and defensible—allowing agencies to confidently use LBS data to support critical planning and policy decisions.
If you’re a transportation planner, modeler, or researcher interested in how LBS data can enhance your work, contact AirSage to learn more about our data, methodologies, and transportation solutions.
