Total Sightings
126,453
Corroborated Events
6,050
Countries
100
Gov Documents
32
Research Papers
12
Shape Distribution
Top Countries
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Geographic Patterns
Regional hotspots and spatial clustering
Temporal Trends
Frequency trends, seasonality, time-of-day, and duration analysis
Shape & Behavior
Morphology classification and movement correlations
Proximity Analysis
Cross-reference with airports, military bases, and satellite passes
Weather Correlation
Actual weather conditions and observational reliability
Gov Document Cross-Ref
AARO, Congressional, and FOIA data analysis
Wave & Flap Detection
Detect concentrated sighting surges across regions and weeks
Strangeness Index
Score sightings, filter out IFOs, analyze the unexplained residual
Witness Narrative Mining
Analyze recurring language and behavioral patterns across accounts
Window Area Detection
Find locations with persistent recurring activity over months
Comparative Study
Side-by-side analysis of two regions, periods, or shape types
Comprehensive Study
Full multi-factor scientific analysis across all dimensions
This comprehensive study analyzes 1,234 cigar-shaped Unidentified Anomalous Phenomena (UAP) sightings reported between January 1, 2020, and March 10, 2026. Utilizing a multi-dimensional analytical framework, we examine geographic distribution, temporal patterns, duration, witness corroboration, and proximity to aviation and military infrastructure. Key findings reveal significant clustering near airports and military installations, a pronounced evening sighting peak, and a low corroboration rate of 11.6%. The study highlights critical data gaps in weather and altitude reporting while establishing a quantitative baseline for this specific UAP morphology.
This study presents a geographic pattern analysis of 278 Unidentified Anomalous Phenomena (UAP) sightings reported between 2026-01-01 and 2026-03-10, with a focus on shapes categorized as Orb, Fireball, and Other. Utilizing aggregated location point data, the analysis identifies statistically significant spatial clusters and corridors, predominantly within the United States. Key findings include a pronounced concentration of reports in the American Southwest and Pacific Northwest, a strong temporal bias toward dusk and night observations, and a notably low corroboration rate of 7.6%. The study evaluates these distributions against potential environmental and infrastructural correlates.
This comparative study analyzes two distinct UAP morphological groups—Orb-shaped (Group A, N=13,018) and Triangle-shaped (Group B, N=2,193)—drawn from a single public reporting database (NUFORC) within the United States from 2018-2026. The analysis identifies a profound disparity in reporting frequency, with Orbs constituting the majority of shaped reports. Despite this volumetric difference, both groups exhibit strong congruence in geographic distribution, diurnal patterns, and event duration profiles. A synchronized anomalous spike in reports for both morphologies in December 2024 points to a potential exogenous stimulus affecting observer behavior. The study concludes that while the reported objects differ in form, the contextual and behavioral patterns of the sightings are largely consistent, suggesting common reporting mechanisms or environmental triggers.
This study presents a narrative analysis of 3,466 witness reports of triangular Unidentified Anomalous Phenomena (UAP) in the United States from January 2015 to March 2026. The research mines 500 textual narratives to identify recurring behavioral descriptions, shared details, and language patterns specific to the 'Triangle' shape type. Key findings include a highly consistent description of a triangular light formation, a strong temporal pattern favoring nocturnal observations, and a low corroboration rate of 9.4%. The analysis suggests a persistent, widely observed phenomenon characterized by specific photometric and kinematic properties.
This study analyzes 3,680 Unidentified Anomalous Phenomena (UAP) reports from January 1, 2025, to March 10, 2026, applying a systematic Strangeness Index to filter out sightings with conventional explanations. The analysis reveals that only 7% (N=259) of reports score as 'high strangeness' (60+). This residual subset is characterized by a predominance of 'Orb' shapes (53.3%), a strong temporal bias toward dusk observations (70.7%), and specific geographic clustering in Florida, Arizona, and California. The findings define a distinct phenomenological profile for the most anomalous cases, which differ significantly from the broader dataset and known IFO patterns.
This study analyzes 373 Unidentified Anomalous Phenomena (UAP) sighting reports from January 1 to March 10, 2026, to identify persistent 'window areas'—geographic locations exhibiting recurring activity over time. Applying a detection threshold of ≥5 sightings across ≥3 distinct months, no qualifying window areas were identified within the dataset. Quantitative analysis reveals a predominance of orb-shaped object reports (49.9%), a strong temporal concentration during dusk hours (52.8% of sightings), and a significant decline in reporting frequency over the study period. The findings highlight the absence of spatially and temporally persistent hotspots in this sample, while underscoring severe data quality limitations inherent in public UAP databases.
This study analyzes 17 Unidentified Anomalous Phenomena (UAP) reports from March 1-10, 2026, focusing exclusively on objects described as 'Orbs'. The analysis examines geographic distribution, witness corroboration, and the inherent limitations of single-witness data for establishing meteorological correlations. Findings indicate a geographically dispersed sample with zero corroboration, presenting significant challenges for assessing observational reliability against localized weather conditions. The study concludes that the dataset is insufficient for robust weather correlation analysis and recommends systematic multi-sensor data collection for future studies.
This study analyzes 11,962 reported sightings of Unidentified Anomalous Phenomena (UAP) categorized as 'Orb' or 'Triangle' shapes from January 1, 2020, to March 10, 2026, to identify correlations with meteorological conditions and assess observational reliability. The analysis reveals a highly non-uniform geographic distribution concentrated in specific U.S. regions and a pronounced, anomalous temporal spike in December 2024. The dataset is characterized by a near-total absence of corroborated events (0.008% corroboration rate) and a predominance of single-witness reports (average 2.2 witnesses). These patterns suggest the data are heavily influenced by sociological and reporting artifacts, complicating the isolation of potential physical or environmental correlates.
This study presents a temporal trend analysis of 1,764 disc-shaped Unidentified Anomalous Phenomena (UAP) reports from January 1, 2020, to March 10, 2026. The analysis focuses on identifying statistically significant patterns in reporting frequency, seasonal cycles, and anomalous surges. The dataset is derived almost exclusively (99.94%) from a single public reporting source. Key findings reveal a pronounced seasonal cycle with a summer peak, a significant anomalous surge in December 2024, and a strong correlation between reporting frequency and human population density. The study provides a quantitative baseline for understanding the socio-temporal dynamics of disc-shaped UAP reporting.
This study analyzes a dataset of 17 Unidentified Anomalous Phenomena (UAP) sighting reports from 1-10 March 2026, cross-referenced with contemporaneous and historical government documentation. The analysis reveals a temporally concentrated, geographically dispersed cluster of single-witness 'Orb' sightings. No direct correlation with specific government events was found within the immediate 10-day window, though the broader context of elevated governmental UAP activity provides a significant backdrop. The findings highlight the challenges of analyzing low-corroboration public data and the importance of temporal context in UAP studies.
This study analyzes the geographic distribution of triangular Unidentified Anomalous Phenomena (UAP) sightings reported between March 1 and March 10, 2026. Utilizing a dataset of nine corroborated sightings from the National UFO Reporting Center (NUFORC), the research employs descriptive spatial statistics to identify distribution patterns. The analysis reveals a diffuse, non-clustered distribution across North America with no statistically significant geographic hotspots or corridors. The findings suggest that, within this limited temporal window, triangular UAP reports do not exhibit spatial clustering that would indicate localized environmental or infrastructural correlates, warranting investigation across broader temporal scales.
This study presents a temporal trend analysis of Unidentified Anomalous Phenomena (UAP) reports specifically describing triangular-shaped objects, occurring between 01 March 2026 and 20 March 2026. The analysis of nine independent reports, sourced exclusively from the National UFO Reporting Center (NUFORC), reveals a concentrated reporting event within a single calendar month, with a geographically dispersed distribution across North America. No corroborated events or significant temporal sub-patterns (e.g., day-of-week effects) were detected within the limited dataset. The findings highlight a discrete cluster of singular-witness reports, suggesting a potential short-term surge in public reporting of a specific UAP morphology.