UAP Sightings Database

The UAP Sightings Database at Skywatcher serves as a centralized repository for recorded observations of Unidentified Anomalous Phenomena (UAP). This system aggregates and catalogs reports from sensor-based detections, civilian and military observations, and independent research organizations. Our objective is to build a comprehensive, structured dataset to facilitate comparative analysis and statistical modeling.

Data Collection & Classification

• Multi-Sensor Integration: Sightings are corroborated through optical, infrared, radar, and RF-spectrum detections.
• Geospatial Mapping: Each sighting is recorded with precise geolocation data and atmospheric conditions at the time of observation.
• Phenomenological Typology: Observations are categorized based on morphological characteristics, motion dynamics, and interaction with the environment.
• Temporal & Pattern Analysis: Detection of recurring trends, high-incidence regions, and anomalous temporal correlations.

Verification & Data Integrity

To maintain the integrity of the database, reported sightings undergo a multi-tier verification process:

• Cross-Referencing with Known Aerospace Activity: Ensuring differentiation from civilian and military aviation, meteorological events, and astronomical objects.
• Algorithmic Anomaly Detection: AI-driven filtering methods assess credibility based on historical patterns and sensor reliability scores.
• Independent Peer Review: Collaborating with scientific institutions to validate high-priority cases.

Purpose & Utilization

The UAP Sightings Database provides researchers with a structured dataset for pattern recognition, statistical correlation, and forensic analysis. By applying computational modeling and machine learning techniques, we aim to extract quantifiable insights into anomalous aerial activity.

Access the latest dataset and contribute to the ongoing refinement of empirical UAP research.