If you were building a mapping application that could show only (say) 20 airports on the screen at once at any given zoom level, how would you decide which airports are most important, using only publicly-available data sets? Here are some possibilities:
- Points for being in the list of the top 100 passenger airports.
- Points for having an ICAO code.
- Points for having an IATA code (rarer, so more points than an ICAO code).
- Points for each localizer and glideslope (since they’re unambiguously associated with the airport).
- Points for having a TAF.
- Points for having a METAR.
- Points for each long, paved runway.
These are all easy to measure, but I’m not sure that they capture enough of what makes an airport important for mapping purposes. Really big airports often cluster around urban areas — think of JFK, EWR, and LGA around New York, or LHR, LGW, and LCY around London. These are all busy airports, but they’re very short drives from each other (traffic permitting), so perhaps they don’t have the same kind of importance on a map as the main airport in a smaller country, the only airport serving an isolated community or an island, etc.
I’ve done some experimenting trying to measure isolation: for example, I’ve tried limiting the map to one airport in each 30×30 deg square (world level) or 10×10 deg square (continent level), but the map still ends up with huge clusters of airports in the U.S. and Western Europe and none in most of the rest of the world, and even a 10×10 square means that Toronto’s and Montreal’s main airports won’t show up (same square as JFK and EWR). What would Google do?