Airport layouts

Data acquisition

Download nodes, ways and relations with the aeroway tag within area marked with various IATA codes. Here in order: Amsterdam, Frankfurt, Paris, San Francisco, New York, Atlanta, Hong-Kong, Osaka Kansai and Singapore.

from cartes.osm import Overpass

airport = Overpass.request(area=dict(iata=iata), aeroway=True)

Data preprocessing

None

Data visualisation

import matplotlib.pyplot as plt
from cartes.crs import Mercator

fig, ax = plt.subplots(
    3, 3, figsize=(15, 15),
    subplot_kw=dict(projection=Mercator())
)

locs = dict(AMS=1, FRA=4, CDG=3, SFO=1, JFK=1, ATL=4, HKG=2, KIX=1, SIN=4)

for ax_, iata in zip(ax.ravel(), locs.keys()):

    # Download data (or get from cache)
    airport = Overpass.request(area=dict(iata=iata), aeroway=True)

    airport.plot(
        ax_,
        by="aeroway",
        # Adjust some colors for this scale
        gate=dict(alpha=0),  # mute
        parking_position=dict(alpha=0),  # mute
        tower=dict(markersize=500),  # reduce
        jet_bridge=dict(color="0.3"),  # change color
        navigationaid=dict(papi=dict(alpha=0)),  # mute
    )
    ax_.spines["geo"].set_visible(False)

    text = AnchoredText(
        iata, loc=locs[iata], frameon=False,
        prop={"size": 24, "fontname": "Fira Sans"},
    )
    ax_.add_artist(text)