You can get all global flight information in 1 API call or track flights based on flight number, airline, departure/arrival airport, and more. The data updates frequently, around every 5 minutes. The details of the data include:

Geography: Location information such as latitude, longitude, altitude, and direction. Speed: Vertical and horizontal speed of aircraft. Departure and arrival: IATA codes and ICAO codes of the departure and arrival airport. Aircraft and flight: IATA and ICAO number of flight and registration number, ICAO code, and ICAO24 code of aircraft. Airline: IATA code, and ICAO code of airline. System information: Squawk, status, and last updated in Epoch.

Here's an example response from the API: [ { "geography": { "latitude": 43.5033, "longitude": -79.1297, "altitude": 7833.36, "direction": 70 }, "speed": { "horizontal": 833.4, "isGround": 0, "vertical": 0 }, "departure": { "iataCode": "YHM", "icaoCode": "CYHM" }, "arrival": { "iataCode": "YQM", "icaoCode": "CYQM" }, "aircraft": { "icaoCode": "B763", "regNumber": "CGYAJ", "icao24": "C08412" }, "airline": { "iataCode": "W8", "icaoCode": "CJT" }, "flight": { "iataNumber": "W8620", "icaoNumber": "CJT620", "number": "620" }, "system": { "updated": 1513148168, "squawk": "0000" }, "status": "en-route" } ]

Developer Information:

1) Available Endpoints &depIata= &depIcao= &arrIata= &arrIcao= &aircraftIcao= &regNum= &aircraftIcao24= &airlineIata= &airlineIcao= &flightIata= &flightIcao= &flightNum= &status= &limit= &lat=&lng=&distance=

2) Flights Tracker API Output

Specific flight based on: Flight IATA Number: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&flightIata=W8519

All flights of a specific Airlines: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&airlineIata=W8

Flights from departure location: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&depIata=MAD

Flights from arrival location: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&arrIata=GIG

Flights within a circle area based on lat and lng values and radius as the distance: GET https://aviation-edge.com/v2/public/flights?key=[API_KEY]&lat=51.5074&lng=0.1278&distance=100&arrIata=LHR

Combinations: two airports and a specific airline flying between them: GET http://aviation-edge.com/v2/public/flights?key=[API_KEY]&depIata=ATL&arrIata=ORD&airlineIata=UA

This dataset provides flight track and aircraft navigation data from the NASA Atmospheric Tomography Mission (ATom). Flight track information is available for the four ATom campaigns: ATom-1, ATom-2, ATom-3, and ATom-4. Each ATom campaign consists of multiple individual flights and flight navigational information is recorded in 10-second intervals. Data available for each flight includes research flight number, date, and start and stop time of each 10-second interval. In addition, latitude, longitude, altitude, pressure and temperature is included at each 10-second interval. NASA's ATom campaign deploys an extensive gas and aerosol payload on the NASA DC-8 aircraft for systematic, global-scale sampling of the atmosphere, profiling continuously from 0.2 to 12 km altitude. Flights occurred in each of 4 seasons from 2016 to 2018. During each campaign, flights originate from the Armstrong Flight Research Center in Palmdale, California, fly north to the western Arctic, south to the South Pacific, east to the Atlantic, north to Greenland, and return to California across central North America. ATom establishes a single, contiguous, global-scale dataset. One intended use of this flight track data is to facilitate to mapping model results from global models onto the precise ATom flight tracks for comparison.

Russia Number of Flights: Domestic data was reported at 67,658.000 Number in Feb 2022. This records a decrease from the previous number of 71,658.000 Number for Jan 2022. Russia Number of Flights: Domestic data is updated monthly, averaging 55,400.000 Number from Jan 2010 (Median) to Feb 2022, with 146 observations. The data reached an all-time high of 127,409.000 Number in Jul 2021 and a record low of 27,413.000 Number in Feb 2010. Russia Number of Flights: Domestic data remains active status in CEIC and is reported by Federal Agency for Air Transport. The data is categorized under Russia Premium Database’s Transport and Telecommunications Sector – Table RU.TE003: Airlines Statistics: Number of Airlines, Aircrafts, Airports and Flights. [COVID-19-IMPACT]

This layer visualizes over 60,000 commercial flight paths. The data was obtained from openflights.org, and was last updated in June 2014. The site states, "The third-party that OpenFlights uses for route data ceased providing updates in June 2014. The current data is of historical value only. As of June 2014, the OpenFlights/Airline Route Mapper Route Database contains 67,663 routes between 3,321 airports on 548 airlines spanning the globe. Creating and maintaining this database has required and continues to require an immense amount of work. We need your support to keep this database up-to-date."To donate, visit the site and click the PayPal link.Routes were created using the XY-to-line tool in ArcGIS Pro, inspired by Kenneth Field's work, and following a modified methodology from Michael Markieta (www.spatialanalysis.ca/2011/global-connectivity-mapping-out-flight-routes).Some cleanup was required in the original data, including adding missing location data for several airports and some missing IATA codes. Before performing the point to line conversion, the key to preserving attributes in the original data is a combination of the INDEX and MATCH functions in Microsoft Excel. Example function: =INDEX(Airlines!$B$2:$B$6200,MATCH(Routes!$A2,Airlines!$D$2:Airlines!$D$6200,0))                                                

The number of flights performed globally by the airline industry has increased steadily since the early 2000s and reached **** million in 2019. However, due to the coronavirus pandemic, the number of flights dropped to **** million in 2020. The flight volume increased again in the following years and was forecasted to reach ** million in 2025.

The Schedules API service provides real-time data for the flight schedules and timetables of airports and airlines around the world and maintains this for you in our central database, always accessible with your personal API key. This is one of Aviation Edge’s core features. You can build real-time airport departure and arrival tables, keep track of delays and cancellations, track the status of flights by using our API. The data comes in JSON format, making it useful to implement to websites and build applications, tools, software, and more.

The data includes the following: - Flight Status: active, scheduled, landed, cancelled, incident, diverted, redirected. - Airport details: IATA code, ICAO code, Terminal, Gate for both departure and arrival airport - Take-off information: Scheduled, estimated and actual times on runway and that of departure/arrival. - Total delay (updated for departures) - Airline: Name, IATA code and ICAO code. - Flight: Number of Flight, IATA prefix with flight number and ICAO prefix with flight number.

Example response from the API:

[ {"airline": {"iataCode":"DL", "icaoCode":"DAL", "name":"Delta Air Lines"}, "arrival": {"actualRunway":"2021-03-03T04:15:00.000", "actualTime":"2021-03-03T04:15:00.000", "baggage":"T4", "delay":null, "estimatedRunway":"2021-03-03T04:15:00.000", "estimatedTime":"2021-03-03T04:15:00.000", "gate":"B41", "iataCode":"JFK", "icaoCode":"KJFK", "scheduledTime":"2021-03-03T05:05:00.000", "terminal":"4"}, "codeshared":null, "departure": {"actualRunway":"2021-03-03T00:10:00.000", "actualTime":"2021-03-03T00:10:00.000", "baggage":5, "delay":"16", "estimatedRunway":"2021-03-03T00:10:00.000", "estimatedTime":”2021-03-03T00:10:00.000”, "gate":"B06", "iataCode":"TLV", "icaoCode":"LLBG", "scheduledTime":"2021-03-02T23:55:00.000", "terminal":"3"}, "flight": {"iataNumber":"DL235", "icaoNumber":"DAL235", "number":"235"}, "status":"landed", "type":"arrival"} ]

Output:

For the departure schedule of a certain airport. GET http://aviation-edge.com/v2/public/timetable?key=[API_KEY]&iataCode=JFK&type=departure

For the arrival schedule of a certain airport. GET http://aviation-edge.com/v2/public/timetable?key=[API_KEY]&iataCode=JFK&type=arrival

Flight data from the US Department of Transportation, Bureau of Transportation Statistics. Downloaded on 2019-07-04. https://www.transtats.bts.gov Data are here for use in software tutorials.

This webpage provides information about the Brazilian Flight Dataset (BFD). The description includes the data sources from regular flights (VRA) and weather data. The VRA is provided by ANAC (Agência Nacional de Aviação Civil) and contains all Brazilian flights. The weather data is provided by ASOS (Automated Surface Observing Systems). ASOS is managed by IOWA University (USA). It contains weather data collected by sensors installed at airports around the world.

The following zip files contain individual flight recorded data in Matlab file format. There are 186 parameters each with a data structure that contains the following: -sensor recordings -sampling rate -units -parameter description -parameter ID

United States No. of Flights: JFK Terminal: 1 data was reported at 35.000 Unit in 16 May 2025. This records a decrease from the previous number of 36.000 Unit for 15 May 2025. United States No. of Flights: JFK Terminal: 1 data is updated daily, averaging 0.000 Unit from May 2008 (Median) to 16 May 2025, with 6215 observations. The data reached an all-time high of 0.000 Unit in 16 May 2025 and a record low of 0.000 Unit in 16 May 2025. United States No. of Flights: JFK Terminal: 1 data remains active status in CEIC and is reported by U.S. Customs and Border Protection. The data is categorized under Global Database’s United States – Table US.TA: Airport Statistics: Number of Flights: by Airport. [COVID-19-IMPACT]

United States No. of Flights: SFO Terminal: A data was reported at 39.000 Unit in 16 May 2025. This records a decrease from the previous number of 47.000 Unit for 15 May 2025. United States No. of Flights: SFO Terminal: A data is updated daily, averaging 29.000 Unit from May 2008 (Median) to 16 May 2025, with 6219 observations. The data reached an all-time high of 65.000 Unit in 31 Mar 2017 and a record low of 0.000 Unit in 31 Aug 2020. United States No. of Flights: SFO Terminal: A data remains active status in CEIC and is reported by U.S. Customs and Border Protection. The data is categorized under Global Database’s United States – Table US.TA: Airport Statistics: Number of Flights: by Airport. [COVID-19-IMPACT]

Graph and download economic data for Enplanements for U.S. Air Carrier Domestic and International, Scheduled Passenger Flights (ENPLANE) from Jan 2000 to Mar 2025 about flight, passenger, air travel, travel, domestic, and USA.

You can connect to the actual flight routes around the world with your API key at any time with very fast response times. It is possible to view all routes at the same time via a single API key. For your convenience, we have also developed many different filters so that you can pull the exact data you are looking for. This way, you may get data of the routes of a specific airline, routes from or to a specific airport (both IATA and ICAO codes work), or may get an individual flight based on its flight number.

A common use of the air routes API is to develop software in the aviation industry. While Aviation Edge’s focus is to collect and maintaining aviation data, you are free to develop countless applications, tools, and platforms by using our data.

The details included in the routes data are: Departure data: IATA code, ICAO code, terminal, and time. Arrival data: IATA code, ICAO code, terminal, and time. Airline: IATA code of airline. Flight: Flight number. Aircraft: Registration number of the aircraft.

Here's an example response from the API: [ { "departureIata": "OTP", "departureIcao": "LROP", "departureTerminal": 2, "departureTime": "09:15:00", "arrivalIata": "TRN", "arrivalIcao": "LIMF", "arrivalTerminal": 1, "arrivalTime": "10:45:00", "airlineIata": "0B", "airlineIcao": "BMS", "flightNumber": "101", "codeshares": null, "regNumber": "YR-BAP" } ]

Developer information: 1) Available Endpoints &departureIata= &departureIcao= &airlineIata= &airlineIcao= &flightNumber=

2) Output Airports, Airlines or Flights routes output: GET http://aviation-edge.com/v2/public/routes?key=[API_KEY]&departureIata=OTP GET http://aviation-edge.com/v2/public/routes?key=[API_KEY]&departureIcao=LROP GET http://aviation-edge.com/v2/public/routes?key=[API_KEY]&airlineIata=0B GET http://aviation-edge.com/v2/public/routes?key=[API_KEY]&airlineIcao=BMS GET http://aviation-edge.com/v2/public/routes?key=[API_KEY]&flightNumber=101 For information about a specific route (example). GET http://aviation-edge.com/v2/public/routes?key=[API_KEY]&departureIata=OTP&airlineIata=0B&flightNumber=101

The historical flight schedule data is perfect to create applications, plugins for websites, running analysis and creating statistics, keeping track of past delays and cancellations for insurance or flight compensation claims, and much more.

We have developed many parameters you can use to pull the exact data you need without having to spend too much time filtering it on your end. We've asked many developers around the world to find out which pieces of data they would need the most, and created the parameters based on this feedback.

The data includes: - Airline: Name, IATA and ICAO codes of the airline. - Departure and arrival: IATA codes and ICAO codes of the departure and arrival location. - Departure and arrival times: Scheduled, estimated and actual arrival and departure times, as well as runway times in local time. - Status: The latest status information of the flight which may be active (for departure schedules), landed (for arrival schedules), cancelled or unknown - Delay: Total delay amount in minutes for delayed flights

Example response from the API: { "type": "departure", "status": "active", "departure": { "iataCode": "jfk", "icaoCode": "kjfk", "terminal": "7", "delay": 10, "scheduledTime": "2020-09-25t20:15:00.000", "estimatedTime": "2020-09-25t20:09:00.000", "actualTime": "2020-09-25t20:25:00.000", "estimatedRunway": "2020-09-25t20:25:00.000", "actualRunway": "2020-09-25t20:25:00.000"}, "arrival": { "iataCode": "lhr", "icaoCode": "egll", "terminal": "5", "scheduledTime": "2020-09-26t08:20:00.000", "estimatedTime": "2020-09-26t07:32:00.000" }, "airline": { "name": "aer lingus", "iataCode": "ei", "icaoCode": "ein" }, "flight": { "number": "8814", "iataNumber": "ei8814", "icaoNumber": "ein8814" }, "codeshared": { "airline": { "name": "british airways", "iataCode": "ba", "icaoCode": "baw" }, "flight": { "number": "114", "iataNumber": "ba114", "icaoNumber": "baw114"} } },

2) Historical Schedules API Output - Developer Information For the departure schedule of a certain airport on a certain date. GET http://aviation-edge.com/v2/public/flightsHistory?key=[API_KEY]&code=JFK&type=departure&date_from=YYYY-MM-DD

For the arrival schedule of a certain airport on a certain date. GET http://aviation-edge.com/v2/public/flightsHistory?key=[API_KEY]&code=JFK&type=arrival&date_from=YYYY-MM-DD

For the schedule of a certain airport of a certain date range (also available for arrival). GET http://aviation-edge.com/v2/public/flightsHistory?key=[API_KEY]&code=JFK&type=departure&date_from=YYYY-MM-DD&date_to=YYYY-MM-DD

For the schedule of a certain airport on a certain date (or range) but only flights with a certain status. GET http://aviation-edge.com/v2/public/flightsHistory?key=[API_KEY]&code=JFK&type=arrival&date_from=YYYY-MM-DD&date_to=YYYY-MM-DD&status=cancelled

For tracking individual historical flights. GET http://aviation-edge.com/v2/public/flightsHistory?key=[API_KEY]&code=JFK&type=departure&date_from=YYYY-MM-DD&date_to=YYYY-MM-DD&flight_number=[1234]

For filtering the flights of a certain airline from the arrival schedule of a certain airport on a certain date (also available for departure schedules and as a date range). GET http://aviation-edge.com/v2/public/flightsHistory?key=[API_KEY]&code=JFK&type=arrival&date_from=YYYY-MM-DD&&airline_iata=TK

Important Tips: - Currently possible to get dates that are up to 1 year earlier than the current date (this will expand soon). - The date range can go up to 28 days for a single API call but may be shorter around 3-5 days for airports with heavy traffic.

NOAA AOC WP-3D Research Flight Data is digital data set DSI-6420, archived at the National Climatic Data Center (NCDC). This data set is meteorological data gathered by Lockheed WP-3D Orion aircraft, operated by the NOAA Aircraft Operations Center (AOC) at MacDill AFB, Florida. Data is provided by the Science and Engineering Division of AOC to the National Climatic Data Center (NCDC). The WP-3D aircraft perform many projects throughout the year. Examples of these projects would be hurricane research, atmospheric chemistry, thunderstorm investigations, and winter weather missions. Each of these projects consists of a series of individual flights. For instance, during hurricane projects, the P-3 may fly numerous flights through different tropical cyclones. For each archived project, there are multiple directories consisting of individual flights. The data in these flight directories contain the actual raw meteorological parameters obtained from sensors located in different positions on the aircraft. The data is initially written to a digital data tape on the aircraft and then later converted to a file for faster processing and archiving. Each flight folder also contains a scanned image of the actual flight manifest, the navigation log, and the mission observation logs. The flight-level data file contains measurements acquired in one second intervals. The following is a generalized list of these measured parameters: Time, GPS position data, inertial data, radar altimeter measurements, liquid water, total temperature, dewpoint temperature, attack pressure, slip pressure, differential attack and slip pressures, and static and dynamic pressure. Depending on the needs of each individual project, other sources of data will be added or subtracted from this list. As of publication this record consists of 5 projects: 1) NOAA-42 Aircraft-N42RF during the 2003 Hurricane season, the Tamdar project, and a wind calibration flight. 2) NOAA-43 Aircraft-N43RF-2003 Sar Pod, Hurricane, and Extratropical Season as well as the SFMR test flight missions. 3) NOAA-49 Aircraft-N49RF 2004 Winter Storms Experiment. 4) NOAA-43 Name Experiment 2004. 5) NOAA-49 Aircraft N49RF Hurricane Season 2004.

The following zip files contain individual flight recorded data in Matlab file format. There are 186 parameters each with a data structure that contains the following: -sensor recordings -sampling rate -units -parameter description -parameter ID

Flight Data Monitoring Market Outlook

The global flight data monitoring market size was valued at USD 3.2 billion in 2023 and is projected to reach USD 6.4 billion by 2032, growing at a compound annual growth rate (CAGR) of 8.2% during the forecast period. This growth is primarily driven by the increasing emphasis on aviation safety and the rising demand for real-time data analytics to enhance operational efficiency. The continuous advancements in flight data monitoring technologies, as well as regulatory mandates for the implementation of safety management systems, are also significant contributing factors.

A major factor propelling the growth of the flight data monitoring market is the stringent regulatory requirements laid down by aviation authorities across the globe. These regulations mandate the deployment of flight data monitoring systems to enhance safety protocols and minimize risks associated with aviation operations. The International Civil Aviation Organization (ICAO) and other regulatory bodies have established guidelines that require airlines to implement robust data monitoring systems, thus driving market demand. Moreover, the increasing incidence of air accidents has led to greater awareness and proactive measures among airlines to adopt comprehensive flight data monitoring solutions.

Technological advancements are another crucial driver for the flight data monitoring market. The advent of innovative technologies such as big data analytics, artificial intelligence, and machine learning has revolutionized the way flight data is collected, analyzed, and interpreted. These technologies enable the real-time monitoring of flight parameters and provide predictive insights that can preempt potential issues, thereby significantly enhancing flight safety and efficiency. The integration of cloud-based solutions has further simplified the process of data storage and retrieval, making it easier for airlines and aviation authorities to access and analyze flight data.

The growing demand for fleet management and operational efficiency is also contributing to the market's expansion. Airlines are increasingly focusing on optimizing their operations to reduce costs and enhance profitability. Flight data monitoring systems provide invaluable insights into various aspects of flight operations, such as fuel consumption, engine performance, and maintenance requirements. This data helps airlines to make informed decisions, improve flight schedules, and enhance overall operational efficiency. Additionally, the adoption of these systems aids in the timely identification of maintenance needs, thereby reducing downtime and associated costs.

The integration of Commercial Aircraft Health Monitoring Systems (CAHMS) is becoming increasingly vital in the aviation industry, especially as airlines strive to enhance their operational efficiency and safety standards. These systems provide real-time data on the health and performance of aircraft components, enabling predictive maintenance and reducing the risk of unexpected failures. By continuously monitoring critical parameters such as engine performance, hydraulic systems, and avionics, CAHMS helps airlines to preemptively address potential issues, thereby minimizing downtime and maintenance costs. The adoption of these systems is driven by the need to improve aircraft reliability and extend the lifespan of fleet assets, aligning with the overarching goals of the flight data monitoring market.

Regionally, North America is expected to dominate the flight data monitoring market, driven by the presence of major airlines and advanced aviation infrastructure. The region's proactive approach to adopting new technologies and stringent regulatory environment further bolster market growth. Europe is also a significant market, with countries like the UK, Germany, and France leading the adoption of flight data monitoring systems. The Asia Pacific region, however, is anticipated to witness the highest growth rate due to the expanding aviation sector in countries like China and India, coupled with increasing investments in aviation infrastructure and safety measures.

Component Analysis

The flight data monitoring market can be segmented by component into hardware, software, and services. The hardware segment encompasses various devices and sensors that are

The following zip files contain individual flight recorded data in Matlab file format. There are 186 parameters each with a data structure that contains the following: -sensor recordings -sampling rate -units -parameter description -parameter ID

The following zip files contain individual flight recorded data in Matlab file format. There are 186 parameters each with a data structure that contains the following: -sensor recordings -sampling rate -units -parameter description -parameter ID

Graph and download economic data for Load Factor for U.S. Air Carrier Domestic and International, Scheduled Passenger Flights (LOADFACTOR) from Jan 2000 to Mar 2025 about flight, passenger, air travel, travel, domestic, and USA.