Placecast™ Airport Enplanements

Airport Enplanements

Motionworks Placecast™ provides visits and enplanements at airport since 2019. These insights are produced with the Motionworks Population Intelligence Platform. Placecast™ is used for investigating visitation trends at locations through time. The following document provides an overview of the validation of Motionworks Airport Enplanements. Motionworks measures visitation and enplanements at 304 airports. Airport visitation and enplanement estimates are scaled to BTS enplanements (BTS | Transtats Airports ). The figure below indicates the distribution of all Motionworks airports across the United States.

Methodology

Source of truth

Motionworks calibrates airport visit estimates against the Bureau of Transportation Statistics (BTS) monthly passenger reports for each airport. The BTS data combines four passenger-flow components:

  • Domestic boardings (passengers boarding flights at this airport)
  • Domestic deplanings (passengers disembarking flights at this airport)
  • International boardings
  • International deplanings

BTS is the public, authoritative measure of US passenger throughput. BTS reports typically arrive at Motionworks with a 2–3 month publication lag from the underlying calendar month.

International Travel

The Motionworks panel data represents domestic device activity. BTS includes all passengers regardless of origin (including international-resident travelers). The BTS factor implicitly closes the international-resident coverage gap by scaling the domestic device counts up to the all-passengers BTS reference.

For airports where international passenger counts arrive later than domestic counts, Motionworks computes an ratio of international/domestic travel from the most recent three months of complete data for that airport and uses it to impute the missing data. Once the actual international figures land in a subsequent BTS report, the imputed values are replaced with the actual data, which could result in revisions of measurements.

Visit categories at airports

The Placecast schema reports several visit categories at Commercial Airports. The four passenger-facing categories are:

  • visits_arrivals — passengers arriving via a flight who depart the airport land-side
  • visits_departures — passengers arriving land-side who depart via a flight
  • visits_transfers — passengers arriving via a flight and departing via a flight (connecting passengers)
  • Other Placecast activity and visit types are also reported, as they are in other Placecast places, but are not passenger flows in the BTS sense; they are people at the airport for other reasons.

Deriving total enplanement

When comparing the Motionworks data to the BTS published passenger count, the equivalent Motionworks total is:

MW enplanement = visits_arrivals + visits_departures + 2 × visits_transfers

Transfer passengers are counted twice because each transfer represents both an arrival (one flight in) and a departure (one flight out) at the same airport, and the BTS passenger total double-counts them for the same reason. This formula is the recommended way to compare Motionworks airport totals against BTS published enplanements + deplanements.

Scaling factor

For each commercial airport where BTS data is available, Motionworks computes one scaling factor per airport per month:

factor[airport, month] = BTS_count[airport, month] / MW_count[airport, month]

  where
    BTS_count = bts_dom_ons + bts_dom_offs + bts_intl_ons + bts_intl_offs
    MW_count  = visits_arrivals + visits_departures + 2 × visits_transfers

This single factor is then applied uniformly to every visit category published at that airport — Arrivals, Departures, Transfers, Workers, Visitors, Residents, and the derived enplanement totals all use the same multiplier. As a consequence, all visit categories at one airport move by the same percent between data releases, because the same factor multiplier rises or falls together for every category at that airport.

What is and is not scaled

SurfaceScaled to BTS?
Visit counts (Arrivals, Departures, Transfers, Workers, Visitors, Residents, Enplanement)Yes — single per-airport monthly factor applied uniformly
Hourly visit profiles (time-of-day distribution)No — derived from observed data
Dwell time (average minutes per visit)No — derived from observed data
Trade-area / home-location distributionNo — derived from observed data
Demographic and segment compositionNo — derived from observed data

Methodology stability

The BTS-factor scaling approach described above is the production method for Motionworks airport enplanements and represents our current and best measurement methodology for the complex nature and data environment of commercial domestic and international airports. Customers can plan on the current behavior — single per-airport monthly factor applied uniformly across all visit categories for the foreseeable future. If and when improvements to the methodology are identified, the change will be announced through the standard release-notes channel, communicated extensively with customers, and reflected on this page.

Airport Stats

Top 25 Airports by BTS EnplanementsBTS Passenger RankMotionworks Monthly Passengers
(Apr 2026)
Motionworks Monthly Passengers
(Jan 2026)
BTS Monthly Passengers
(Jan 2026)
Difference Ratio (%)Motionworks Monthly Passengers
(Apr 2025)
BTS Monthly Passengers
(Apr 2025)
Hartsfield- Jackson Atlanta International Airport1 / 304103,5207,462,5337,318,5472.0%8,483,4688,549,586
Dallas- Fort Worth International Airport2 / 30484,7166,012,6575,850,4252.8%6,451,0806,483,797
Denver International Airport3 / 30480,9965,841,7455,719,4502.1%6,022,4456,050,740
Chicago O'Hare International Airport4 / 30478,6865,634,3085,506,7352.3%6,377,1796,432,146
Los Angeles International Airport5 / 30475,0825,532,5475,429,9001.9%5,964,3616,002,367
Orlando International Airport6 / 30461,7194,866,8514,803,1631.3%4,777,9634,811,536
Miami International Airport7 / 30459,5014,824,3604,795,9780.6%4,430,6994,446,949
John F Kennedy International Airport8 / 30460,9584,369,8354,277,0452.2%5,098,6255,145,086
Phoenix Sky Harbor International Airport9 / 30455,5714,069,2773,994,4281.9%4,440,9494,460,254
Harry Reid International Airport10 / 30453,5723,934,2823,879,9851.4%4,496,6904,539,024
San Francisco International Airport11 / 30453,3313,834,2443,750,3922.2%4,261,8134,297,449
George Bush Intercontinental Airport12 / 30450,5913,671,6113,594,2382.2%3,624,7273,637,032
Newark Liberty International Airport13 / 30450,3043,560,3053,470,5412.6%3,805,9173,824,018
Seattle - Tacoma International Airport14 / 30448,6793,488,3683,411,9472.2%3,953,1913,979,818
Charlotte Douglas International Airport15 / 30449,2303,469,0043,376,0162.8%4,449,7764,483,065
Fort Lauderdale/ Hollywood International Airport16 / 30467,2723,002,2482,953,1521.7%2,734,8992,752,602
General Edward Lawrence Logan International Airport17 / 30438,6962,720,5692,644,3052.9%3,597,0903,628,035
Minneapolis - St Paul International/ Wold - Chamberlain Airport18 / 30433,6042,427,8172,384,2311.8%2,806,3712,814,994
Laguardia Airport19 / 30433,1482,317,9862,253,6082.9%2,737,6902,752,408
Detroit Metropolitan Wayne County Airport20 / 30431,5922,254,1602,205,2022.2%2,658,6282,675,671
Salt Lake City International Airport21 / 30426,9872,102,6052,080,0971.1%2,153,9942,158,536
Philadelphia International Airport22 / 30427,0061,914,8521,864,1052.7%2,546,2602,577,171
San Diego International Airport23 / 30426,6841,902,7621,855,7722.5%2,028,2302,044,497
Tampa International Airport24 / 30425,5511,886,5281,843,9792.3%2,182,6922,198,106
Washington Dulles International Airport25 / 30426,9231,874,0591,813,9663.3%2,338,7262,364,915

Airport Charts