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.

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.

Dataset

This dataset was created by Ioana Gheorghiu

Contents

Explore the historical Whois records related to flight-data-animation.com (Domain). Get insights into ownership history and changes over time.

A. SUMMARY San Francisco International Airport (SFO) keeps track of historical flight operations, also known as aircraft RADAR data for analysis and reporting.

B. HOW THE DATASET IS CREATED Details of flights from the Federal Aviation Administration’s National Offload Program are processed into SFO’s Airport Noise and Operations Management System (ANOMS) where it is correlated with noise reports from the communities and to noise levels collected from noise monitor sites on the San Francisco Peninsula. In ANOMS, various analysis gates (imaginary vertical curtain in space) are used to identify which route flights flew departing and arriving SFO. It serves to quantify, analyze, respond to noise concerns, and report on Runway Use and various programs to reduce aircraft noise in communities surrounding SFO.

C. UPDATE PROCESS Data is available starting in August 2019 and will be updated monthly.

D. HOW TO USE THIS DATASET It is important to note, that this dataset is of flights departing and landing at SFO only and not flight activities associated with other airports in the Bay Area region. This information is the data source used to produce the Flight Operations sections (pages 3-5) of the Airport Director’s Report. These reports are presented at the SFO Airport Community Roundtable Meetings and available online at https://noise.flysfo.com/reports/?category=airport-directors-report

E. RELATED DATASETS Unique Flight Operations - This filtered view contains unique records of flight operations. For example, one record for a flight that departed SFO or one record for a flight that landed at SFO.

Arrival and Departure Routes - This filtered view contains records of flights with details of analysis gate(s) the aircraft flight track penetrates, to derive which route was used to depart and land at SFO.

This dataset contains Operations and Arrival and Departure Routes joined on operation_number. The field gate_penetration is derived by ordering the arrival and departure routes for each operation over gate_penetration_time. Unique_identifier is then created by joining operation_number and gate_penetration.

Other provided datasets are Aircraft Noise Reports, Late Night Aircraft Departures, Air Carrier Runway Use, and Late Night Preferential Runway Use, Aircraft Noise Climates, and Noise Exceedance Rating.

Please contact the Noise Abatement Office at NoiseAbatementOffice@flysfo.com for any questions regarding this data.

Date created: November 17, 2023

A. Usecase/Applications possible with the data:

1. Maintain a competitive pricing strategy: Learn how your competitors have priced their tickets in order to stay competitive in the market with the best prices. You can also plan how to offer discounts and low-cost rooms based on the availability of your competitors' packages.

2. Systemize your services: Use the data to better serve your customers by systemizing your services by i) Scheduling flights based on market demand and supply ii) Understanding your customers' sentiments and preferences.

3. Stay on top of availability: Optimize seat or ticket availability by thoroughly researching the supply in the market as well as the offerings of your competitors.

How does it work?

• Analyze sample data
• Customize parameters to suit your needs
• Add to your projects
• Contact support for further customization

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

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))                                                

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.

India All Scheduled Airlines: Domestic: Number of Flight data was reported at 102,319.000 Unit in Mar 2025. This records an increase from the previous number of 92,291.000 Unit for Feb 2025. India All Scheduled Airlines: Domestic: Number of Flight data is updated monthly, averaging 48,100.000 Unit from Apr 2001 (Median) to Mar 2025, with 288 observations. The data reached an all-time high of 102,319.000 Unit in Mar 2025 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.

Brazil Air Passenger Traffic: International Flight: Regular data was reported at 715,238.000 Person in Jul 2022. This records an increase from the previous number of 594,201.000 Person for Jun 2022. Brazil Air Passenger Traffic: International Flight: Regular data is updated monthly, averaging 747,581.000 Person from Jan 2008 (Median) to Jul 2022, with 175 observations. The data reached an all-time high of 1,175,884.000 Person in Jan 2019 and a record low of 21,090.000 Person in Apr 2020. Brazil Air Passenger Traffic: International Flight: Regular data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under Global Database’s Brazil – Table BR.TAB025: Passenger Traffic: Summary. [COVID-19-IMPACT]

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.

United States Exports of aircraft, spacecraft to Ecuador was US$54.91 Million during 2024, according to the United Nations COMTRADE database on international trade. United States Exports of aircraft, spacecraft to Ecuador - data, historical chart and statistics - was last updated on July of 2025.

According to Cognitive Market Research, the global Aviation Analytics Marketsize is USD 4.6 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 13.5% from 2024 to 2031. Market Dynamics of Aviation Analytics Market Key Drivers for Aviation Analytics Market Increasing Adoption of 5G Networks Drives the Aviation Analytics Market- The growing deployment of 5G networks is likely to drive the aviation analytics industry. 5G networks are the fifth generation of wireless technology for cellular communications. They are intended to provide much higher data rates, lower latency, and increased network capacity than prior generations (e.g., 4G LTE). 5G networks offer much faster data transmission speeds and lower latency than previous generations. This allows for faster and more efficient data transfers, which is critical for real-time analytics in the aviation industry. For instance, CRISIL, an India-based capital market organisation, predicts that by March 2025, 300 million Indians, or approximately one-third of all cellular subscribers, will be using 5G. Increased aviation passenger traffic drives growth in the aviation analytics market Key Restraints for Aviation Analytics Market A shortage of experienced analytics specialists stifles market growth Data security concerns will stymie market growth Introduction of the Aviation Analytics Market Aviation involves activities related to the aircraft industry and mechanical flight. Analytics is the systematic computer analysis of statistics or data. Aviation analytics is a computer system that provides end users with information or statistics derived from past airport operating data, historical flight data, weather predictions, and real-time flight data. It enables predictive analysis and query processing of massive aviation data. It mostly provides forecasts or solutions based on enormous aviation data, both organised and unstructured. Moreover, the global aviation analytics market is being driven by a growing emphasis on competitive intelligence and real-time analytical solutions to improve corporate productivity. Furthermore, the constant growth in the volume of data generated in the aviation industry, the surge in airline passenger traffic, and the increase in customer centricity all contribute to the market's growth

United States Exports of aircraft, spacecraft to Ireland was US$1.62 Billion during 2024, according to the United Nations COMTRADE database on international trade. United States Exports of aircraft, spacecraft to Ireland - data, historical chart and statistics - was last updated on July of 2025.

United States Imports of aircraft, spacecraft from Palau was US$14.16 Thousand during 2019, according to the United Nations COMTRADE database on international trade. United States Imports of aircraft, spacecraft from Palau - data, historical chart and statistics - was last updated on June of 2025.

United States Exports of aircraft, spacecraft to Iceland was US$210.45 Million during 2024, according to the United Nations COMTRADE database on international trade. United States Exports of aircraft, spacecraft to Iceland - data, historical chart and statistics - was last updated on June of 2025.

United States Exports of aircraft, spacecraft to Cyprus was US$81.39 Million during 2024, according to the United Nations COMTRADE database on international trade. United States Exports of aircraft, spacecraft to Cyprus - data, historical chart and statistics - was last updated on July of 2025.

United States Imports from Venezuela of Aircraft, spacecraft was US$208.41 Thousand during 2024, according to the United Nations COMTRADE database on international trade. United States Imports from Venezuela of Aircraft, spacecraft - data, historical chart and statistics - was last updated on July of 2025.

United States Exports of aircraft, spacecraft to Thailand was US$568.89 Million during 2024, according to the United Nations COMTRADE database on international trade. United States Exports of aircraft, spacecraft to Thailand - data, historical chart and statistics - was last updated on June of 2025.