Top Questions MPOs Ask About Mobile Device-Based Origin-Destination Data 

As Metropolitan Planning Organizations (MPOs) expand their use of location-based services (LBS) data, many ask the same practical questions about coverage, accuracy, privacy, and how this data complements existing sources. Below, we answer the most common questions MPOs ask AirSage about LBS-based Origin-Destination (O-D) data.

1.) We already use O-D data derived from connected vehicles, why do we need LBS data as well?

LBS data fills important gaps left by other mobility data sources. In particular, it helps MPOs better understand:

• • Travel mode (car, bike, transit, air)
  • Trip purpose
  • Trip frequency and chaining
  • Home locations of travelers, enabling resident vs. visitor analysis
  • Cross-border traffic

Many agencies use LBS data alongside other datasets to gain a more complete picture of travel behavior.

2.) Can LBS data be used to see full trips?

Yes, when processed correctly. AirSage reconstructs complete origin-to-destination trips using anonymized and probabilistic methods. We never track or identify Individual devices, and we only deliver outputs in aggregate. This allows MPOs to analyze full trip patterns without compromising privacy.

3.) What defines a trip?

A trip is defined as movement between two stationary points. AirSage identifies stationary points using behavior-based algorithms rather than simple distance or time thresholds. In general, a trip occurs when a device travels between two meaningful locations and exhibits dwell time consistent with an activity. This approach produces trip definitions that more closely reflect real-world travel behavior as understood by transportation planners.

4.) How do you determine home and work locations?

AirSage infers home and work location through longitudinal analysis of recurring overnight and daytime dwell patterns observed over multiple days. The process is probabilistic, statistically validated, and results are aggregated and anonymized, allowing MPOs to analyze resident versus visitor travel while maintaining strong privacy protections.

5.) At what granularity is your data available?

AirSage location-based services (LBS) data is available at multiple spatial and temporal resolutions and is customizable based on project needs. These resolutions include:

• Geography: TAZs, census block groups, census tracts, counties, corridors, points, and custom polygons
• Time: Hourly, peak vs. off-peak, weekday/weekend, seasonal, or user-defined periods
• Trip characteristics: Origin–destination, distance, duration, mode, and inferred trip purpose

This flexibility allows MPOs to integrate the data directly into travel demand models, Long Range Transportation Plans (LRTPs), and special studies.

6.) What days and time periods should MPOs use?

The appropriate days and time periods depend on the planning question. Common best practices include:

• Multi-week or multi-month averages for stable results
• Typical weekdays for commute-focused analysis
• Weekends or seasonal periods for tourism and recreational travel
• Peak periods for congestion and reliability studies

Using longer analysis windows helps reduce noise and improve representativeness.

7.) What data metrics does your O-D Trip Matrix include?

Our O-D Trip Matrix includes metrics such as average trip counts between origin and destination zones, travel times, and travel distances. These metrics help planners better understand travel patterns and regional mobility trends. 

8.) How far back in time does your historical data go?

AirSage maintains a consistent historical archive dating back to 2018. This supports:

• Multi-year trend analysis
• Before-and-after studies
• Model calibration and validation
• Retrospective evaluations of policy or infrastructure changes

9.) How do you account for GPS drift and poor reception?

AirSage applies multiple quality-control techniques, including map-matching, smoothing algorithms, accuracy scoring, and behavioral logic to filter out noise. Rather than relying on individual GPS points, the methodology focuses on repeatable movement patterns, which improves reliability for planning and modeling applications.

In areas with weak reception, GPS pings are still recorded by the device. The location data is temporarily stored and then transmitted once the device reconnects to cellular service, helping preserve trip continuity even when real-time connectivity is interrupted.

10.) Is your data privacy-compliant?

AirSage is committed to protecting consumer privacy through the use of anonymized, aggregated mobility data and strict data governance practices. We collect location data only from users who have opted in to share their information through mobile applications. All delivered datasets are de-identified and aggregated, ensuring that no personally identifiable information (PII) is included.

Why MPOs Use AirSage Mobility Data

AirSage mobile device-based O-D data helps MPOs understand who is traveling, where they are going, how they travel, and how patterns change over time—with greater scale and flexibility than traditional surveys and counts alone. As planning questions grow more complex, trip-based LBS data has become an essential component of the modern MPO toolkit.

Interested in learning more or requesting sample data? Contact the AirSage team at transportation@airsage.com.