Mumbai Case Study

What the sky over Mumbai looks like

I wanted a simple answer to a real question: what is flying over Mumbai, when does it feel busy, and where does it slow down?

Scope: first day of each month from --, within a 1500 km radius around Mumbai. The charts and tables come from a local SQLite bundle, so the page loads quickly and stays fixed.

What matters if you live in Mumbai

Quick answers first, then the details.

How the day feels

Local time, weekday rhythm, and daypart mix.

Local hour traffic | IST 24-hour clock

Local hour traffic

Local hour speed | IST 24-hour clock

Local hour speed

Weekday pattern

Weekday pattern

Dayparts

Dayparts

Local hour charts use Mumbai time in a 24-hour clock. 00:00 is midnight, 12:00 is noon.

Where it slows down

Close-in traffic, low altitude traffic, and the slowest pockets near the city.

Distance bands

Speed by distance

Altitude bands

Speed by altitude

Sector speed

Speed by sector

Slow cells

Slow cells near Mumbai

Vertical behavior

How much of the sample is cruise, climb, or descent.

Vertical motion phases

Vertical motion phases

Yearly shape

Growth, recovery, and the COVID-era dip.

Monthly trend

Monthly trend

Yearly trend

Yearly trend

Who is likely in the sample

These are inferred from callsigns and should be read as probable airline prefixes, not official airline records.

Likely airline prefixes

Likely airline prefixes

Inferred flow direction

Inferred flow direction

Inferred sector routes

Inferred sector routes

The airline view is a prefix match from callsigns. The flow view is a sector-to-sector approximation from the first and last sightings of a sampled track.

Interpretation

Plain language from the bundle, not dashboard jargon.

Tables

A compact view of the same patterns with the numbers spelled out.

Distance bands

Altitude bands

Sector view

Year by year

Regular visitors

Likely airline prefixes

Flow mix

Inferred routes

How I read this

One short read first, then the structure behind it.

Aircraft identity and limits

Hex is a transponder address. Airline labels come from callsign prefixes. Route flow is inferred, not filed.

Hex

The hex code is the aircraft's ICAO24 address - a unique transponder identifier. It tells me which aircraft I am seeing, but not the airline on its own.

Callsign

The callsign is the operational label shown in the data. I use the prefix to infer a likely airline, which is useful for pattern reading but still a guess.

Flow route

The route section is built from the first and last sightings in each sampled track, then grouped by sector and distance band. It shows movement shape, not official origin-destination pairs.

That is the short version: hex is the aircraft, callsign is the label, airline is inferred, and routes are corridor patterns.

Method and limits

Enough detail to trust the shape of the result without pretending it is more precise than it is.

  • Sample scope: first day of each month, centered on BOM / VABB, within a 1500 km radius.
  • Airline labels: inferred from callsign prefixes only. Useful for pattern-spotting, not as official airline truth.
  • Route flow: inferred from the first and last sector seen for a track. It is directional movement, not filed origin/destination.
  • Interpretation: this is a monthly sampling scheme. It is good for trends and comparisons, not full-month precision.

Query Console

Run a small SQL query against the trimmed observatory tables. This is not the 300 MB source DB, just the parts that are useful for exploration.

Loading tables...
Run a query to see a table result.