Documents / Official release
This is a 2023 draft research paper by Richard M. Medina and Simon Brewer of the University of Utah and Sean M. Kirkpatrick of the Department of Defense, prepared for journal submission and released in full by AARO in 2025. It analyzes 98,724 NUFORC public sighting reports from 2001 to 2020 by county with a Bayesian model. It finds that more light pollution and tree canopy mean fewer sightings, while more air traffic and military area mean more. Cloud cover showed no relationship.
025 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 Unidentified Areal Phenomena (UAP). All data preparation and calculations are made using Microsoft Excel and ESRI ArcGIS Pro software. To aid in interpretation, all covariates were z- score transformed prior to modeling. Light pollution – The data source for light pollution is the New World Atlas of Artificial Sky Brightness (Falchi et al., 2016a; Falchi et al., 2016b). This raster data set is offered in a geotiff file with 30 arcsecond/1km resolution and covers the entire world. For this project the data for the U.S. were extracted and the mean value for light pollution (values represent simulated zenith radiance in [mcd/m2]) was calculated for each U.S. county. Cloud cover – Cloud cover data are sourced to the EarthEnv Project (Wilson and Jetz, 2016). These data are compiled using 15 years (2000-2014) of twice-daily remotely sensed observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. They are provided in a geotiff file at 1km resolution for the entire world. The cloud cover values were averaged for each U.S. county. Tree canopy – The tree canopy data are from the Multi-Resolution Land Characteristics Consortium (Coulston et al., 2012; Coulston et al., 2013). The data are generated by the United States Forest Service (USFS) using Landsat imagery and “other available ground and ancillary information” (Multi-Resolution Land Characteristics Consortium, 2022). The values represent 2016 vegetation at 30m resolution and are available for the continental U.S., coastal Alaska and Hawaii. Because of the size of the file and the resolution of other datasets in the model, the image required resampling. They were upsampled to 1km resolution. The tree canopy values were then averaged for each U.S. county. Airports – These data are provided by ESRI’s, ArcGIS Online service accessible through the ArcGIS Pro software. They include categories for airports, heliports, seaplane bases, ultralights, gliderports, balloonports and other. There are 19,850 entries in this dataset. Each entry is represented as a point. The data are standardized here as the number of airports per sq. km.Page determined to be Unclassified Reviewed by Chief of Staff, AARO IAW FY24 NDAA, Section 1841 (a)(1)(C) Date: 02/06/2025
Official release, from the nara collection. The PDF is mirrored here; the original link is above. 16 pages are in the text index: search them above, or from the library's search.