-
Notifications
You must be signed in to change notification settings - Fork 1
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Use FlightRadar24 etc. to get additional Data #24
Comments
FYI: E-Mail has been sent to them, still waiting on an answer. |
@arebe337 About the PAX numbers on all the routes, we could also take the approach of estimating the average available seats on a all routes using FlightRadar24 like I did here. We take the aircraft types from FR24 and average the available seats, then assuming an average load factor we could derive an estimate for number of PAX. This approach has several implications:
|
@dodedic what would we get from this Tier 3 call? |
So I could provide a table of data @arebe337 , just like the one @michaelweinold suggested here. Where we have the "average" available seats for each route in this format. Then using your script which uses the amount of flights we can put it together to give us the estimate of PAX. Like I mentioned above we benchmark the data using routes where we know the annual PAX traffic. The API call I would use is this one. It's a Tier 3 request which we have 150'000 of still. In this request get the destination and the aircraft type (but crucially not the amount of flights...so the work done so far is still important). I will first make a list of all aircraft types and attach an average available seats to it. |
We could also trial this approach by using one specific route again first, if the Lagos-Abuja example from here is not convincing enough. @michaelweinold Would love to hear your input on this method/estimation before I get to coding and making API calls. |
So, @dodedic, are you referring to the 'Flight status' call in this scenario? The link you provided directs to the 'FIDS (airport departures and arrivals) - by relative time / by current time' call. I'm unsure where that one would display the type of aircraft. But that approach could indeed give us a reliable approximation! |
If we then use this call. This would give us the exact number of seats on that flight. This is a Tier 1 call, of which we have 200'000. Now let's say we request data for this one aircraft with this registration and we store it as well. Then if we see that on a next flight it's again this aircraft, we simply use the stored value and not make a new API request. This would avoid us burning through too many API requests. With the current worldwide airliner fleet size around 20'000-30'000 aircraft this should work out. |
Alright, that sounds like a plan! I would be really happy if you could do this part:) |
Ofcourse! I will do it gladly 😄 |
Possible issue I see: |
I agree, it shouldn't pose a major issue. However, we do need to consider our approach for handling such cases. We should definitely identify the month with the highest number of different connections and prioritize that month. But I also agree, taking into account different seasons could also be beneficial for a more comprehensive analysis. |
You can use the table I created with my last master's student: ...but as per your more recent comment #24 (comment), it seems that you can go though all active aircraft and just get the exact number of seats.
So in this example, you have 473 departures, all(?) of which are from a single aircraft
So the |
Exactly, we get all the active aircraft.
Actually we get all departures from LSZH in the selected timeframe, one of which happened to be the HB-JJK. All other flights are from other airlines and other aircraft.
It returns (among other information) the destination of each flight departing the airport within the specified timeframe, as well as the exact aircraft registration and type of aircraft as seen in this comment's screenshot. This means we can either take the general aircraft type and estimate via your compiled list. Or we make an API call with ADB as mentioned above in order to get the exact number of seats on that flight.
This meant that the |
I am currently updating the Mermaid diagram to visualize this process! |
Since AeroDataBox alone likely won't provide enough information to estimate the number of passenger on specific routes, we can use data from FlightRadar24 (or other sourcea) in addition.
Conveniently, there is already a Python package wrapping the API: FlightRadarAPI
I am feeding data to the site, so I have an active Business Subscription. This is required for API access. However, it seems from the documentation that they don't have historical data in the API at the moment. If this really is the case, we might need to look for data "manually" in the FlightRadar24 data archive.
There is also pyflightdata and the ADSBExchange API.
@dodedic, I suggest you contact the ADSBExchange team about the possiblity of receiving a data dump of historical data (perhaps for the case-studies):
The text was updated successfully, but these errors were encountered: