Anomalous Sightings Archive

Project Overview

This project investigates potential correlations between Bigfoot and UFO (UAP) sightings across the United States. The primary question is whether there is a meaningful relationship in time and/or location, or whether geographic clusters appear when the two report streams are compared.

Secondary goals include shared environmental conditions — season, weather, and geomagnetic Kp index — and practical notes for independent investigators. Patterns here are observational. They do not establish a causal link between the two phenomena.

Stack: Python, Jupyter, Pandas, SQLite, Matplotlib, Seaborn, GeoPandas, Folium, Open-Meteo, and GFZ Kp index data.

View the repository · Open the main notebook · Interactive dashboard

Key Findings

Proximity clusters

Reports that land close together in space show concentrations in the Pacific Northwest (strongest), Northern California, the Ohio Valley, Central Arkansas, and Florida.

Scatter map of Bigfoot and UAP reports in close proximity across the United States — Proximity map — paired reports from the SQLite `proximity` table.

Location

Bigfoot reports concentrate in forested regions, especially the West Coast and Eastern U.S., with a notable gap across the Central Plains and western deserts. UAP reports are more even nationwide, with clusters in the Pacific Northwest, Montana, and Vermont.

Population-weighted map of UAP reports in the contiguous United States — UAP reports, population-density weighted, contiguous U.S.

Timing

UAP sightings peak around 9:00–10:00 p.m.
Both Bigfoot and UAP reports peak in summer and early fall (roughly June–November).
UAP report volume rises sharply from the mid-1990s.
Bigfoot reports increase more gradually across the dataset years.

Bar chart showing 24 distribution of UAP sightings data — UAP Sightings - Over 24 Hours

Line chart of UAP and Bigfoot reports per year from 1950 to 2013 — Reports per year, 1950–2013.

Environmental conditions

Cloud cover: a large share of UAP reports occur under clear skies (0–10%). Bigfoot reports are more even across cloud-cover ranges.
Temperature: averages are similar; Bigfoot reports trend slightly cooler (≈56.8 °F vs. ≈60.1 °F for UAP).
Kp index: both report types show a higher share of events during quiet geomagnetic conditions (Kp 0–1) than the historical baseline.

Bar chart showing cloud cover distribution of Bigfoot and UAP reports — Reports By Cloud Cover %

Histogram comparing temperatures at Bigfoot and UAP sightings

Bar chart comparing Kp index distribution for historical conditions, Bigfoot reports, and UAP reports

Maps & Charts

Static outputs from the analysis notebook. Click any figure to open the full image.

Methods

Raw NUFORC UAP reports, BFRO Bigfoot reports, and U.S. Census population data are cleaned in Pandas, enriched with geohashes, haversine distances, Open-Meteo weather (2011 UAP sample), and GFZ Kp index values, then loaded into SQLite.

bigfoot_reports, uap_reports, states
proximity (composite key: bf_id + uap_id)
kp_index, weather tables for Bigfoot and 2011 UAP reports

Entity relationship diagram for the anomalous sightings SQLite database — SQLite entity-relationship diagram.

Sources: NUFORC, BFRO, U.S. Census, GFZ Kp Index, Open-Meteo.

Interactive front end

This page is the static project face: narrative, findings, and saved maps. The next step is a Streamlit dashboard for year, state, distance, and weather filters on the same SQLite tables.

Dashboard coming soon — analysis lives in the repo for now

Run it locally

Clone, create a venv, install requirements.txt, then Run All on notebooks/anomalous_sightings_analysis.ipynb. The notebook rebuilds processed data, the SQLite database, and the files in plots/.