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25_Sky_View_Final_Draft.pdf

NARA·UAP_Bulk_Downloads·pdf·2.6 MB·16 pages

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Anomalousness

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Public UAP Sightings and the Environment: An Analysis 
of Sky View Potential 
Richard M. Medina 
University of Utah 
Simon Brewer 
University of Utah 
Sean M. Kirkpatrick 
Department of Defense 
Proposed journal for submission: Annals of the American Association of Geographers 
Introduction 
There has been growing interest by the United States government in Unidentified 
Anomalous Phenomena (UAP). Given the new focus on this potential security threat and the 
operational safety risks posed by these objects, the UAP Task Force was initiated on August 4, 
2020 (U.S. Department of Defense, 20
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DNI report summarizes that there is no single explanation for all of these UAP, with potential 
sources including clutter, commercial drones, national security threats, and other unexplained 
phenomena. In 1969, another government effort, Project Blue Book determined that 701 
sightings out of 12,618 were “unidentified,” but that there was no evidence of 1) any national 
security threat, 2) advanced technologies beyond present capabilities or knowledge, and 3) 
extraterrestrial vehicles (U.S. Air Force, nd). While there are some logical explanations for what 
many are seeing, that they thi
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Much of the research on UAPs has relied on firsthand accounts, psychological 
explanations, or specific events, which limits the systematic analysis of large area patterns (e.g., 
see Zimmer, 1984; Zimmer, 1985; Spanos et al., 1993; Salisbury, 1974). Data availability for 
large studies has been a longstanding issue, and the few studies that exist focus on smaller scale 
patterns and trends. 
The most likely explanation for a portion of UAP sightings is natural phenomena. For 
example, the planet Venus is the brightest planet and is often mistaken for a UAP. At times, it is 
seen close to 
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Maybe the most popular natural explanation for UAP sightings is ball lightning. Ball 
lightning incidents are characterized by “a spherical or roughly spherical light-emitting object 
whose size varies from a few cm to a meter or more, with an average diameter of about 20 cm, 
and whose colors vary from red to yellow, white, blue, and (rarely) green” (Shmatov and 
Stephan, 2019, p. 1). Ball lightning is a rare event and data on its occurrences often relies on 
eyewitness accounts. These events are believed to most often occur at or near an ongoing 
thunderstorm. One of the issues with the 
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were given, but were still locatable, when spelling errors in the city field were corrected. For 
those, coordinates were added using online Microsoft services to construct a more complete 
dataset. The final resulting mappable dataset includes 121,949 points (locatable in the United 
States), which is 99.16% of the total extraction. For simplicity and interpretation, we focus on 
the conterminous U.S. from 2001 to 2020, which reduces the number of reported sightings to 
98,724. For the analysis we use the total number of sightings per county across this time period 
to allow us to focus o
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Figure 2 NUFORC Reported Sighting Spatial Distribution for the Conterminous U.S. from 
2001-2020 
In the spatial sciences, data like these are typically referred to as Volunteered 
Geographical Information (VGI). VGI are geographic information that are volunteered either 
knowingly or unknowingly by individuals, typically with the assistance of location enabled 
digital tools (Goodchild, 2007), and the issues connected to the use of these datasets has been 
extensively discussed. Those vulnerabilities are present here, along with others given the nature 
of this dataset. Like with other cr
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the only dataset of this size and detail that allows for geographic research. Furthermore, it is 
impossible to discredit over 120,000 cases. It should also be mentioned here that NUFORC 
accepts online, phone, and written reports to assist in unbiasing the dataset with only online 
activity. 
Explanatory Variables 
We use 3 explanatory datasets to represent physical and built environment attributes that 
would restrict the view of the sky: light pollution, cloud cover, and tree canopy cover. 
Additionally, we use 2 datasets that represent added airborne activity that might be mistaken for
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Military installations – Military installation data are sourced to U.S. Census TIGER/Line 
shapefiles and downloaded from data.gov (data.gov, 2022). The U.S. Census created this dataset 
in collaboration with the U.S. Department of Defense and the U.S. Department of Homeland 
Security. The data represent the boundaries of military installations. For this research, those 
boundaries were overlaid onto U.S. counties, where the area of each county that is military 
installation is calculated. 
Models 
The NUFORC dataset is first explored alone to identify general spatial patterns of 
reported

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