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

Projections of commercial airline flight schedules worldwide. Describe characteristics of each flight such as: departure and arrival airports, flight times, carrier, fares, capacity, and more. Projections are made at the beginning of every time period (month or year) and project the schedules for that time period until the next update is received. Data from 1979-March 1987 are available monthly. Data from 1987 onward are available annually.DATA AVAILABLE FOR YEARS: 1978-2024 (see Note for specifics)

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.

The Future Schedules API is perfect for: • Travel agency and flight booking websites where users are expected to submit a date and view available flights • Websites, tools or apps to display scheduled flights on a given date • Flight schedule and airway traffic analysis based on region or dates

We have developed many filters you can use in the input to request the exact data you need without having to filter the data on your end.

The data includes: - Departure and arrival airport information: IATA codes - Weekday: The day of the week of the flight, "1" being Monday - Terminal and gate: The most common terminal and the gate number of the departing/arriving flight - Take-off information: Scheduled departure or arrival time of the flight - Aircraft details: Model code and text - Airline details: Name, IATA and ICAO codes - Flight information: Flight number with flight IATA and ICAO codes

1) Request For the departure schedule of a certain airport on a certain future date.

GET http://aviation-edge.com/v2/public/flightsFuture?key=[API_KEY]&type=departure&iataCode=BER&date=YYYY-MM-DD

For the arrival schedule of a certain airport on a certain future date.

GET http://aviation-edge.com/v2/public/flightsFuture?key=[API_KEY]&type=arrival&iataCode=BER&date=YYYY-MM-DD

For the flights that are scheduled to arrive at a certain airport on a certain date (out of a departure schedule).

GET http://aviation-edge.com/v2/public/flightsFuture?key=[API_KEY]&type=departure&iataCode=BER&arr_iataCode=ORY&date=YYYY-MM-DD

For the flights that are scheduled to depart from a certain airport on a certain date (out of an arrival schedule).

GET https://aviation-edge.com/v2/public/flightsFuture?key=[API_KEY]&type=arrival&iataCode=BER&dep_iataCode=ory&date=YYYY-MM-DD

2) Filters &iata_code= (obligatory) Departure or arrival airport IATA code depending on the "&type=" value &type= (obligatory) Either "departure" or "arrival" as both within the same query is not possible &date= (obligatory) Future date in YYYY-MM-DD format

&dep_iataCode= filter of departure airport if "arrival" for "&type=" was chosen, based on the airport IATA code &dep_icaoCode= filter of departure airport if "arrival" for "&type=" was chosen, based on the airport ICAO code &arr_iataCode= filter of arrival airport if "departure" for "&type=" was chosen, based on the airport IATA code &arr_icaoCode= filter of arrival airport if "departure" for "&type=" was chosen, based on the airport ICAO code &airline_iata= option to filter airline based on airline IATA code &airline=icao= option to filter airline based on airline ICAO code &flight_num= option to filter a specific flight based on its flight number

3) Example Output: [ {"weekday": "1", "departure": { "iataCode": "mty", "icaoCode": "mmmy", "terminal": "c", "gate": "f2", "scheduledTime": "20:35" }, "arrival": {"iataCode": "iah", "icaoCode": "kiah", "terminal": "d", "gate": "d12", "scheduledTime": "22:00" }, "aircraft": {"modelCode": "a320", "modelText": "airbus a320-232" }, "airline": {"name": "vivaaerobus", "iataCode": "vb", "icaoCode": "viv"}, "flight": {"number": "616", "iataNumber": "vb616", "icaoNumber": "viv616"} } ]

Note: Schedules that are up to 1 year ahead of the current date are available.

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

Bi-Annual Data Exposition: Every other year, at the Joint Statistical Meetings, the Graphics Section and the Computing Section join in sponsoring a special Poster Session called The Data Exposition , but more commonly known as The Data Expo. All of the papers presented in this Poster Session are reports of analyses of a common data set provided for the occasion. In addition, all papers presented in the session are encouraged to report the use of graphical methods employed during the developme nt of their analysis and to use graphics to convey their findings. Airline on-time performance: Have you ever been stuck in an airport because your flight was delayed or cancelled and wondered if you could have predicted it if you'd had more data? This is your chance to find out. The data: The data consists of flight arrival and departure details for all commercial flights within the USA, from October 1987 to April 2008. This is a large dataset: there are nearly 120 million records in total, and takes up 1.6 gigabytes of space compressed and 12 gigab ytes when uncompressed. The data comes originally from RITA where it is described in detail. You can download the data there, or from the bzipped csv files listed below. These files have derivable variables removed, are packaged in yearly chunks and have been more heavily compressed than the originals. Variable descriptions: Name Description 1 Year 1987-2008 2 Month 1-12 3 DayofMonth 1-31 4 DayOfWeek 1 (Monday) - 7 (Sunday) 5 DepTime actual departure time (local, hhm m) 6 CRSDepTime scheduled departure time (local, hhmm) 7 ArrTime actual arrival time (local, hhmm) 8 CRSArrTime scheduled arrival time (local, hhmm) 9 UniqueCarrier unique carrier code 10 FlightNum flight number 11 TailNum plane tail number 12 ActualElapsedTime in minutes 13 CRSElapsedTime in minutes 14 AirTime in minutes 15 ArrDelay arrival delay, in minutes 16 DepDelay departure delay, in minutes 17 Origin origin IATA airport code 18 Dest des tination IATA airport code 19 Distance in miles 20 TaxiIn taxi in time, in minutes 21 TaxiOut taxi out time in minutes 22 Cancelled was the flight cancelled? 23 CancellationCode reason for cancellation (A = carrier, B = weather, C = NAS, D = security) 24 Diverted 1 = yes, 0 = no 25 CarrierDelay in minutes 26 WeatherDelay in minutes 27 NASDelay in minutes 28 SecurityDelay in minutes 29 LateAircraftDelay in minutes

India All Scheduled Airlines: International: Number of Flight data was reported at 18,574.000 Unit in Jan 2025. This records an increase from the previous number of 18,324.000 Unit for Dec 2024. India All Scheduled Airlines: International: Number of Flight data is updated monthly, averaging 7,783.000 Unit from Apr 2001 (Median) to Jan 2025, with 281 observations. The data reached an all-time high of 18,574.000 Unit in Jan 2025 and a record low of 273.000 Unit in May 2020. India All Scheduled Airlines: International: Number of Flight data remains active status in CEIC and is reported by Directorate General of Civil Aviation. The data is categorized under India Premium Database’s Transportation, Post and Telecom Sector – Table IN.TA019: Airline Statistics: All Scheduled Airlines.

India All Scheduled Airlines: Domestic: Number of Flight data was reported at 99,013.000 Unit in Dec 2024. This records an increase from the previous number of 94,818.000 Unit for Nov 2024. India All Scheduled Airlines: Domestic: Number of Flight data is updated monthly, averaging 47,900.000 Unit from Apr 2001 (Median) to Dec 2024, with 285 observations. The data reached an all-time high of 99,013.000 Unit in Dec 2024 and a record low of 188.000 Unit in Apr 2020. India All Scheduled Airlines: Domestic: Number of Flight data remains active status in CEIC and is reported by Directorate General of Civil Aviation. The data is categorized under India Premium Database’s Transportation, Post and Telecom Sector – Table IN.TA019: Airline Statistics: All Scheduled Airlines.

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 ASIAS effort builds on demonstrations that an open exchange of information contributes to improved aviation safety. ASIAS is a comprehensive effort, covering the collection and secure maintenance of aviation data, the analysis performed on that data, and long-term research to better extract safety information from the data. In the mid-90s, NASA researchers started briefing the JIMDAT of CAST on how extracting and integrating information from many sources, and multiple perspectives (including controllers and flight crews) could help them improve aviation safety. The NASA Integrated Safety Data for Strategic Response (ISDSR) concept was incorporated into the JIMDAT concept, ASIAS, which was presented to CAST as essential capabilities, and was then adopted. In parallel with these activities, the FAA encouraged NASA to undertake the Information Sharing Initiative (ISI), a collaborative effort among FAA, NASA, the air carriers and the unions, to develop the DNFA and DNAA (two key srouces of data for ASIAS). A 5-yr plan for collaboration between NASA and the FAA to develop ISDSR was proposed, but was never put into place. That plan would have continued the collaboration with provisions for NAS to develop the analytical tools and transfer them to the FAA for implementation. NASA has, and continues to, develop advanced algorithms to mine the various data sources for information that could continue to maintain and improve the safety of the air transportation system. Such algorithms have already been developed by NASA to identify atypical flights revealing unexpected events and etermine why they were anomalous, to identify anomalous cockpit procedures (switches flipped in the cockpit) during takeoff and landing for possible evidence of problems with the automated systems, and to categorize submitted safety reports such as those submitted to ASRS or ASAP into one or more defined categories to aid the search for clues as to why safety-related events may have occurred. ASIAS provides a vital mechanism for monitoring for safety concerns as we transition to the Next Generation Air Transportation System (NextGen). Not only can ASIAS examine for any indication of hypothesized concerns, but, with the NASA-developed data mining tools, ASIAS can also monitor for statistical trends suggesting the potential emergence of new issues unanticipated or unimagined during the design and testing of NextGen concepts. ASIAS has been carefully developed to capitalize upon the best attributes of earlier research at NASA, while also providing necessary guarantees for anonymity and data protection and while using scientifically justified, rigorous methods for estimating frequencies and causality. NASA's role in the ASIAS effort is to continue to develop these advanced data mining tools and methods to better analyze data voluntarily provided by the aviation community. Acronym List: ASAP: Aviation Safety Action Program ASRS: Aviation Safety Reporting System ASIAS: Aviation Safety Information Analysis & Sharing CAST: Commercial Aviation Safety Team FAA: Federal Aviation Administration ISDSR: Integrated Safety Data for Strategic Response ISI: Information Sharing Initiative JIMDAT: Joint Implementation Monitoring Data Analysis Team NASA: National Aeronautics and Space Administration

Graph and download economic data for Revenue Passenger Miles for U.S. Air Carrier Domestic and International, Scheduled Passenger Flights (RPM) from Jan 2000 to Nov 2024 about flight, miles, passenger, air travel, travel, revenue, domestic, and USA.

China Air: General Flight Time: Industry data was reported at 89,336.000 Hour in 2017. This records an increase from the previous number of 82,875.000 Hour for 2016. China Air: General Flight Time: Industry data is updated yearly, averaging 44,873.000 Hour from Dec 1990 (Median) to 2017, with 21 observations. The data reached an all-time high of 96,354.000 Hour in 2013 and a record low of 19,850.000 Hour in 1990. China Air: General Flight Time: Industry data remains active status in CEIC and is reported by Civil Aviation Administration of China. The data is categorized under China Premium Database’s Transportation and Storage Sector – Table CN.TI: Air: Flight Hour.

Graph and download economic data for Available Seat Miles for U.S. Air Carrier Domestic and International, Scheduled Passenger Flights (ASM) from Jan 2000 to Nov 2024 about flight, miles, passenger, air travel, travel, domestic, and USA.

Münster/Osnabrück Airport provides information about the current arrival and departure situation at the FMO via this dataset. The data is provided as a machine-readable XML interface. Update of flight data Flight data shall be updated and made available in the interface with each change. The information that can be accessed via the XML interface thus represents the current situation at the airport. More information Documentation of the XML fields used in the interface can be obtained by clicking on the XML icons (see above) or in the PDF file “Instructions on how to use the XML interface”. If you have any other questions about the interface or if you have any questions about the Open Data Portal, please contact the City of Münster’s Open Data Coordination (contact below). Further information about Münster/Osnabrück Airport can be found on the airport’s homepage at www.fmo.de FMO Flughafen Münster/Osnabrück GmbH provides data to the best of its knowledge and belief. In some cases, third party data are published via the airport. The liability of the airport is limited to intent and gross negligence.

Total Scheduled Flight: United States: Salinas, California-Hong Kong SAR (China) data was reported at 1.000 Unit in 13 May 2019. Total Scheduled Flight: United States: Salinas, California-Hong Kong SAR (China) data is updated weekly, averaging 1.000 Unit from May 2019 (Median) to 13 May 2019, with 1 observations. The data reached an all-time high of 1.000 Unit in 13 May 2019 and a record low of 1.000 Unit in 13 May 2019. Total Scheduled Flight: United States: Salinas, California-Hong Kong SAR (China) data remains active status in CEIC and is reported by VariFlight. The data is categorized under China Premium Database’s Transportation and Storage Sector – Table CN.TM: VariFlight Flight Statistics: Total Scheduled Flight: Arrival: Hong Kong SAR (China).

Flight Data

Total Scheduled Flight: Guangdong: Guangzhou-South Africa: Johannesburg data was reported at 1.000 Unit in 28 Oct 2019. This stayed constant from the previous number of 1.000 Unit for 07 Oct 2019. Total Scheduled Flight: Guangdong: Guangzhou-South Africa: Johannesburg data is updated weekly, averaging 1.000 Unit from Sep 2019 (Median) to 28 Oct 2019, with 5 observations. The data reached an all-time high of 2.000 Unit in 30 Sep 2019 and a record low of 1.000 Unit in 28 Oct 2019. Total Scheduled Flight: Guangdong: Guangzhou-South Africa: Johannesburg data remains active status in CEIC and is reported by VariFlight. The data is categorized under China Premium Database’s Transportation and Storage Sector – Table CN.TM: VariFlight Flight Statistics: Total Scheduled Flight: Departure: Guangdong.

China Total Scheduled Flight: United States: Anchorage, Alaska-Beijing data was reported at 1.000 Unit in 01 Apr 2024. This stayed constant from the previous number of 1.000 Unit for 04 Nov 2019. China Total Scheduled Flight: United States: Anchorage, Alaska-Beijing data is updated weekly, averaging 1.000 Unit from Jul 2019 (Median) to 01 Apr 2024, with 4 observations. The data reached an all-time high of 1.000 Unit in 01 Apr 2024 and a record low of 1.000 Unit in 01 Apr 2024. China Total Scheduled Flight: United States: Anchorage, Alaska-Beijing data remains active status in CEIC and is reported by VariFlight. The data is categorized under China Premium Database’s Transportation and Storage Sector – Table CN.TM: VariFlight Flight Statistics: Total Scheduled Flight: Arrival: Beijing.

CN: Total Scheduled Flight: Russian Federation: Yekaterinburg-Inner Mongolia: Erdos data was reported at 1.000 Unit in 30 Dec 2019. This stayed constant from the previous number of 1.000 Unit for 23 Dec 2019. CN: Total Scheduled Flight: Russian Federation: Yekaterinburg-Inner Mongolia: Erdos data is updated weekly, averaging 1.000 Unit from Oct 2019 (Median) to 30 Dec 2019, with 9 observations. The data reached an all-time high of 2.000 Unit in 25 Nov 2019 and a record low of 1.000 Unit in 30 Dec 2019. CN: Total Scheduled Flight: Russian Federation: Yekaterinburg-Inner Mongolia: Erdos data remains active status in CEIC and is reported by VariFlight. The data is categorized under China Premium Database’s Transportation and Storage Sector – Table CN.TM: VariFlight Flight Statistics: Total Scheduled Flight: Arrival: Inner Mongolia.

China Total Scheduled Flight: United States: Honolulu, Hawaii-Beijing data was reported at 6.000 Unit in 30 Dec 2019. This records an increase from the previous number of 5.000 Unit for 23 Dec 2019. China Total Scheduled Flight: United States: Honolulu, Hawaii-Beijing data is updated weekly, averaging 6.000 Unit from Dec 2018 (Median) to 30 Dec 2019, with 52 observations. The data reached an all-time high of 12.000 Unit in 04 Feb 2019 and a record low of 1.000 Unit in 16 Sep 2019. China Total Scheduled Flight: United States: Honolulu, Hawaii-Beijing data remains active status in CEIC and is reported by VariFlight. The data is categorized under China Premium Database’s Transportation and Storage Sector – Table CN.TM: VariFlight Flight Statistics: Total Scheduled Flight: Arrival: Beijing.