Well, the definition of beauty differs for everyone, cant blame you for that, but maybe i can explain where i see the beauty in it: just by counting positions of flights and visualizing them a map of the world emerges, its something we didnt expect to happen at all and it fascinated me, and if the world isnt beautiful, what is?

I do understand you though, its really not the prettiest visualization, its rough and there may even be some faulty data in it, but it is my data and my visualization, made trough my work, thats what makes it pretty for me

that would deff be an explanation, maybe we will find out more about that if we take another look at the data, maybe we just made a mistake in our code, ill deff keep that in mind tho

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thanks a lot! we already submitted the project and got a perfect grade for it, dont know if the US uses the same system but it was a 1.0, this bitmap is just one small part of the statistics that our program did

yeah, true, i dont know how to explain that discrepancy. All i can say is that we not only collected passenger flights but basically anything that transmitted ADS-B. Im also not sure how exactly the FAA is doing their statistics. We also counted the tracking points itself and not the flights, so there may be more tracking points over miami, maybe more flights are circling there while waiting to be cleared for landing or something like that, but of course Atlanta and LA are still the busiest airports. Honestly: I dont know, but you brought up an interesting point that none of us noticed during the creation of it, thanks for that!, ill probably try searching for the max value pixels

not sure what you are referring to, but none of the data comes from Wikipedia or the Mediawiki-foundation, it was all collected by us using data we grabbed from Flightradar24 and our own ADSB-Receivers

The data was collected in may of 2022 over the span of two to three weeks iirc, its been a while so im not exactly sure anymore.

Id explain the apparent low flight volume by the way in which we calculated the pixel values, we basically took the "quadrant" with the most flights and set that as 255, every other "quadrant" was then calculated as a percentage of that and that was translated back to an integer value between 0 and 255.

Since the US is incredibly busy regarding the amount of flights it might have blown that maximum value out of proportions and therefore everywhere else is "underrepresented", but you can still see that china is pretty busy, also there is the himalaya north of india, west of china where i guess not many planes are flying as well as the gobi desert a bit north of china, you can also clearly make out japan and indonesia. Personally i find it quite interesting that you can make out Ukraine by the missing of flights entirely

As to miami, im really not sure, id interpret the data as such as that miami does not only seem busy, it IS busy, id have to look up our airport statistics but the US had the most "most frequented airports" by a long shot, we were also more focused on europe since thats where we are from, iirc LAX was the busiest of them all

This data was collected by a program we wrote as a university project, we collected Data from Flightradar24 and our own ADS-B receiver

The Data is visualized as a bitmap where the value of the pixel correspond to the relative amount of planes in the area compared to the area with the highest amount of planes using the rule of three, where [highest amount] equals a value of 255. This is our most detailed Bitmap, the data was collected over the time of a few weeks, with roughly 1.4 million tracking-datasets in our Database. We also visualized the Data in Minecraft, although the script does get a few things wrong currently

We divided the world in "quadrants" of a fixed size, about the size of 0.05° by 0.05° iirc and counted how many trackingpoints where in those quadrants