Geospatial · Case Study 02

Mapping UFO Reports Across America

Where 80,000 sightings cluster, when they spike, and what those patterns actually measure.

GeospatialTime-series forecastReal NUFORC data
Live map + forecast + notebook
The question

Across 80,000 real sighting reports: where do they cluster, when do they spike, and can the volume of future reports be forecast? And the question that keeps the project honest, what do those patterns actually measure?

The data

Real reports from NUFORC, the National UFO Reporting Center (via the TidyTuesday project), spanning 1925 to 2014. Messy like any report log: international rows and missing coordinates to filter out, placeholder shapes like na and unknown, and free-text timestamps to parse into a year, month, hour, and weekday.

The approach

Geospatial aggregation and a live scatter map of the real coordinates, then temporal decomposition across month, hour, weekday and calendar date, then a log-linear trend model fit to the online era with a proper train/test backtest, then a transparent likelihood model that scores any month, day and hour.

What it found

Hotspots follow population, not the paranormal: California, Washington, Florida, Texas and New York lead. The sharpest signal is the clock, with reports peaking at 9 to 10 pm. The season peaks in July, the week peaks on Saturday, and the Fourth of July is the single busiest date by a wide margin. Report volume grew about 10% a year through the internet era. Every one of those patterns has an ordinary explanation, which is exactly the point: the model describes human reporting behavior, not real events.

80,327
reports analyzed
+10.2%
report growth / year
±18%
backtest error (MAPE)
5.9×
peak-slot likelihood
Skills demonstrated
geospatial analysistime-series forecastingbacktestingtemporal decompositiondata cleaningEDAcanvas data vizhonest framingmodel interpretation