Graph and download economic data for Public Transit Ridership (TRANSIT) from Jan 2000 to Apr 2025 about public, transportation, and USA.

The number of public transport passengers has been on a slow upward trend and is projected to reach *** billion users by 2029. This upward trend was interrupted between 2020 and 2022, due to the COVID-19 pandemic, when user numbers dropped significantly and then began recovering to the pre-pandemic levels.

This dataset supports measure M.C.3 of SD 2023. The sources of data are the American Community Survey and Capital Metro. Each row displays the percent of population in a census tract block group that has access to innovative public transit service, or is within a quarter mile of regular fixed route transit. This dataset can be used to understand the percentage of population that has access to innovative public transit service or is within a quarter mile of a regular fixed transit route. View more details and insights related to this data set on the story page: https:https://data.austintexas.gov/stories/s/Percentage-of-population-that-has-access-to-innova/3agy-grwi/

This study includes the number of public transit stops per United States census tract or ZIP code tabulation area (ZCTA) based on data from the National Transit Map (NTM). Each observation represents the count and density (per capita and square mile) of transit stops within a census tract or ZIP code tabulation area (ZCTA), as voluntarily reported to NTM between 2016-2018 and 2024 by one of 270 regional transit agencies choosing to participate.

In 2022, the number of incidents reported throughout the public transit networks in the U.S. amounted to ****** events, a year-over-year increase of ** percent. In the past decade, the number of transit incidents peaked in 2016 at ****** occurrences and reached an all-time low amid the pandemic in 2020 at a record of ******.

United States - Public Transit Ridership was 616783.00000 Thous. of Unlinked Trips in January of 2025, according to the United States Federal Reserve. Historically, United States - Public Transit Ridership reached a record high of 993437.00000 in May of 2007 and a record low of 171450.00000 in April of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Public Transit Ridership - last updated from the United States Federal Reserve on July of 2025.

Large urban transit, monthly total revenue and total number of passenger trips, for the 10 major Canadian urban transit operators.

This data view shows the proximity to public transportation, and modal share of commuters by metropolitan city.

This lists datasets published by CTA in the City of Chicago Data Portal.

This table contains data on the percent of residents aged 16 years and older mode of transportation to work for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Census Bureau, Decennial Census and American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Commute trips to work represent 19% of travel miles in the United States. The predominant mode – the automobile - offers extraordinary personal mobility and independence, but it is also associated with health hazards, such as air pollution, motor vehicle crashes, pedestrian injuries and fatalities, and sedentary lifestyles. Automobile commuting has been linked to stress-related health problems. Active modes of transport – bicycling and walking alone and in combination with public transit – offer opportunities for physical activity, which is associated with lowering rates of heart disease and stroke, diabetes, colon and breast cancer, dementia and depression. Risk of injury and death in collisions are higher in urban areas with more concentrated vehicle and pedestrian activity. Bus and rail passengers have a lower risk of injury in collisions than motorcyclists, pedestrians, and bicyclists. Minority communities bear a disproportionate share of pedestrian-car fatalities; Native American male pedestrians experience four times the death rate Whites or Asian pedestrians, and African-Americans and Latinos experience twice the rate as Whites or Asians. More information about the data table and a data dictionary can be found in the About/Attachments section.

*** DISCLAIMER - This web page is a public resource of general information. The Maryland Mass Transit Administration (MTA) makes no warranty, representation, or guarantee as to the content, sequence, accuracy, timeliness, or completeness of any of the spatial data or database information provided herein. MTA and partner state, local, and other agencies shall assume no liability for errors, omissions, or inaccuracies in the information provided regardless of how caused; or any decision made or action taken or not taken by any person relying on any information or data furnished within. *** This dataset assesses rail station potential for different forms of transit oriented development (TOD). A key driver of increased transit ridership in Maryland, TOD capitalizes on existing rapid transit infrastructure. The online tool focuses on the MTA’s existing MARC Commuter Rail, Metro Subway, and Central Light Rail lines and includes information specific to each station. The goal of this dataset is to give MTA planning staff, developers, local governments, and transit riders a picture of how each MTA rail station could attract TOD investment. In order to make this assessment, MTA staff gathered data on characteristics that are likely to influence TOD potential. The station-specific data is organized into 6 different categories referring to transit activity; station facilities; parking provision and utilization; bicycle and pedestrian access; and local zoning and land availability around each station. As a publicly shared resource, this dataset can be used by local communities to identify and prioritize area improvements in coordination with the MTA that can help attract investment around rail stations. You can view an interactive version of this dataset at geodata.md.gov/tod. ** Ridership is calculated the following ways: Metro Rail ridership is based on Metro gate exit counts. Light Rail ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. MARC ridership is calculated using two (2) independent methods: Monthly Line level ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. This method of ridership calculation is used by the MTA for official reporting purposes to State level and Federal level reporting. Station level ridership is estimated by using person counts completed by the third party vendor. This method of calculation has not been verified by the FTA for statistical reporting and is used for scheduling purposes only. However, because of the granularity of detail, this information is useful for TOD applications. *Please note that the monthly level ridership and the station level ridership are calculated using two (2) independent methods that are not interchangeable and should not be compared for analysis purposes.

Includes New York City MTA Subway, San Francisco BART Rail, Washington Metropolitan Area Transit Authority Bus and Rail

Employment statistics on the Public Transportation industry in the US

Provides transit agency-wide totals for service data for applicable agencies reporting to the National Transit Database in the 2022 and 2023 report years. This view is based off of the "2022 - 2023 NTD Annual Data - Service (by Mode and Time Period)" dataset, which displays the same data at a lower level of aggregation. This view displays the data at a higher level (by agency).

NTD Data Tables organize and summarize data from the 2022 and 2023 National Transit Database in a manner that is more useful for quick reference and summary analysis. The parent dataset is based on the 2022 and 2023 Service database files.

In years 2015-2021, you can find this data in the "Service" data table on NTD Program website, at https://transit.dot.gov/ntd/ntd-data.

In versions of the data tables from before 2014, you can find data on service in the file called "Transit Operating Statistics: Service Supplied and Consumed."

If you have any other questions about this table, please contact the NTD Help Desk at NTDHelp@dot.gov.

A monthly measure of the volume of services performed by the for-hire transportation sector. The index covers the activities of local mass transit, intercity passenger rail, and passenger air transportation.

This layer depicts the public transportation lines received through the Esri Community Maps program, USDOT, and publicly available datasets from agencies, municipalities and countries around the world. It is designed to be used with the other World Transit layers in the Living Alas. These layers include:World Transit Agency CentroidsWorld Transit StopsWorld Transit Lines by ModalityThese transit layers can be accessed together through the following resources:World Transit Group LayerWorld Transit Web MapWorld Transit Viewer (Web Mapping Application)The public transit lines are symbolized using color codes (six digit hexadecimal) provided by transit agencies. These colors correspond to many agencies" color designations such as in the Washington DC Metro with the Red, Orange, Blue, Green Yellow and Silver lines. The transit data is received in the General Transit Feed Specification (GTFS) format, an open data standard for public transportation data. Each GTFS dataset is a zipped archive of comma-separated files describing the transit services, including the geometry for mapping. Esri converts GTFS datasets into ready-to-use map layers and makes them available as Feature Services in the Living Atlas. Esri Transit map layers include data from Esri Community Maps contributors, the US Department of Transportation, as well as publicly available GTFS datasets. Please note that any data layer fields marked with an "(Esri)" tag have been added by Esri to provide user-friendly translations of GTFS standard values or to add additional context and value. Community Maps GTFS dataThrough the Esri Community Maps Program, transit organizations are able to submit their own GTFS data for use across the ArcGIS platform, giving their data more visibility and accessibility to users. Organizations interested in sharing their data can join the Community Maps Program as a data contributor. Community Maps transit contributors include:Utah Transit AuthorityWeGo Public Transit - Nashville, TNUMass AmherstSpokane Transit Authority - Spokane, WAGrand County, COMETRO HoustonLee County, FLBay of Plenty Regional Council (NZ)Miami-Dade CountyRTC Southern NevadaLA Metro - Los Angeles, CAIMPLAN - Chihuahua, MexicoSunTran - Tucson, AZVIA Metropolitan Transit - San Antonio, TXCape Breton Regional Municipality - Nova Scotia, CanadaWashington County Transit Department - Washington County, MDEastern Panhandle Transit Authority - Martinsburg, WVNew Orleans Regional Transit Authority - New Orleans, LAPark County Transit - Park County, MTMetro Cali S.A. - Cali, Colombia (CO) USDOT National Transportation Map DataData is included from the United States Department of Transportation (USDOT), Bureau of Transportation Statistics (BTS) National Transit Map (NTM) National Transportation Atlas Database (NTD) where the data is not available from Esri Community Maps contributors. A full list of NTM contributing entities is available at https://geodata.bts.gov/maps/national-transit-map-agencies. Most agencies" data are in the public domain except for the following, which are licensed under the Creative Commons by Attribution 3.0 (CC BY 3.0) license. Data accessed on Feb 6, 2024 from National Transit Map Routes.USDOT NTM CC BY 3.0 ContributorsGreater Peoria Mass Transit DistrictCity of GlendoraCity of DelanoCity of Sierra VistaCity of AvalonCity of LawndaleChemehuevi Indian TribeVia Mobility ServicesMiddletown Transit DistrictRockland Coaches IncKootenai CountySpokane Tribe of IndiansWaccamaw Regional Transportation AuthorityDillions Bus Service IncUnified Human Services Transportation Systems Inc Publicly Available GTFS DatasetsMetropolitan Council - Metro Transit - Minneapolis/St Paul, MN (Public Domain)Minnesota Valley Transit Authority (Public Domain)AC Transit - Bay Area, CA (Public Domain)OVapi Netherlands GTFS (NL) (Custom open licensing terms)Open Bus Data (UK) (Contains public sector information licensed under the Open Government License v3.0)Swiss Open Transport Data (CH) (Open data license)Japanese Public Transportation Data - Kyoto, Kyoto Prefecture (JP) (Public Transportation Open Data Basic License)Transport for New South Wales (AU) (CC BY 4.0)Victoria Department of Transport and Planning (AU) (CC BY 4.0)Department for Infrastructure and Transport - South Australia (AU) (CC BY 4.0)Otago Regional Council (NZ) (CC BY 4.0)Ireland National Transport Authority (IE) (CC BY 4.0)Metrolink - Southern California (US) (CC BY 3.0)DELFI German GTFS Data (DE) (CC BY 4.0)ENTUR (NO) (Contains data under the Norwegian licence for Open Government data distributed by Entur.org)MITRAMS (ES) (Government of Spain - Ministry of Transport and Sustainable Mobility)Department of Transport, Goa (IN) (Directorate Of Transport, Government Of Goa)Hyderabad Metro Rail Limited (IN) (Contains data provided by Hyderabad Metro Rail Ltd.)Canadian Public Transit Network (CA) (Contains information licensed under the Open Government Licence – Canada)

DVRPC tracks transit ridership in the region through unlinked passenger trips, with data provided by each of the region's four transit operators—Southeastern Pennsylvania Transportation Authority (SEPTA), New Jersey Transit (NJ Transit), Port Authority Transit Corporation (PATCO), and Pottstown Area Rapid Transit (PART)—to the National Transit Database (NTD). Unlinked passenger trips count each passenger boarding, regardless of fare paid. Thus, a trip with a transfer would count as two boardings. Transit ridership does not include Amtrak, shuttles, or private bus passengers. It also does not include services that receive partial funding from SEPTA, like SCCOOT operated by the Transportation Management Association of Chester County.

One table shows the number of unlinked trips by mode—bus, trolley bus, light rail, heavy rail, commuter or regional rail, and non-scheduled services, which includes paratransit, demand response, and vanpools. All NJ Transit services are classified as being in the NJ Counties Subregion, because they mostly do not cross over to the Pennsylvania side of the region. The other table shows the number of unlinked trips by transit agency. The region's commuter rail services are mostly in the PA Suburban Counties Subregion. SEPTA is the only agency in the region with trolleybus services. SEPTA classified the Norristown High Speed Line (NHSL) as a subway, which travels through the PA Suburban Counties Subregion. SEPTA's subway services travel within the city of Philadelphia. Because of how these subway services cover multiple subregions, subways were simply classified as being in the DVRPC Region. Also, both tables contain: Total unlinked trips, unlinked trips per capita, unlinked trips per vehicle revenue hour (VRH), and unlinked trips per vehicle revenue mile (VRM). Vehicle revenue hours and miles count only when transit vehicles are operating along their scheduled routes. These figures do not account for ‘deadhead’ miles when not in passenger service, such as going to and from the depot on their way to or coming back from their scheduled route. Heavy rail and commuter rail services that operate with multiple passenger vehicles in one train count miles and hours for each vehicle individually. For example, a train with six passenger cars traveling one mile will count as six vehicle revenue miles.

NJ Transit's ridership figures are for the DVRPC region only. These figures are based on service in the Trenton and Philadelphia urbanized areas collected by the NTD. Prior to 2013, NJ Transit ridership, vehicle revenue hours, and vehicle revenue miles data was only provided at the statewide level. To calculate the region’s share of these NJ Transit figures, statewide totals from 1997 to 2012 were multiplied by the region’s percentage based on the 2013 to 2022 averages in each category. These averages were 12% of the state's total ridership, 14% of the vehicle revenue miles, and 12% of the vehicle revenue hours. PART ridership data is only available from 2005 onwards. PART vehicle revenue hour and mile data is only available from 2011 onwards. SEPTA trolley bus ridership data is not available from 2004 to 2007.

Fixed route bus includes commuter bus, motor bus, bus rapid transit, and trolleybus. The Federal Highway Administration estimates monthly transit ridership, released as part of the National Transit Database. Ridership estimates have been adjusted to account for changes in data collection over time. Starting in January 2012, data for Small System Waiver agencies that do not have a mode are reported under motor bus. Data reported under hybrid rail are reported under their classifications prior to January 2012.

This deprecated dataset provides systemwide ridership and traffic estimates for subways (including the Staten Island Railway), buses, Long Island Rail Road, Metro-North Railroad, Access-A-Ride, and Bridges and Tunnels, beginning 3/1/2020, and provides a percentage comparison against a comparable pre-pandemic date.

Next-day estimates for daily ridership, without the pre-pandemic comparison, are now provided at https://data.ny.gov/d/sayj-mze2

Financial overview and grant giving statistics of American Public Transportation