Detecting Great Power Competition Through Geospatial Analysis: A North American Arctic Case Study

Simple item page
dc.contributor.advisorRice, Matthew
dc.contributor.authorValentine, James A
dc.creatorValentine, James A
dc.date2021-04-30
dc.date.accessioned2023-01-12T23:58:05Z
dc.descriptionThis thesis has been embargoed for 5 years and will not be available until April 2026 at the earliest.
dc.description.abstractThe current era of Great Power Competition (GPC) between the People's Republic of China (PRC), the Russian Federation (Russia), and the United States is characterized by increased use of \hybrid threats." These are actions, short of military force, that are designed to fall under existing detection and response thresholds and compromise existing security norms and decision making processes. National security scholars and practitioners widely agree that the ability of the United States and its allies to detect and respond to these hybrid threats is limited at best, and that the Indication and Warning (I & W) intelligence function, designed to prevent strategic surprise that fundamentally alters policy, plans, and assumptions about the security environment, has atrophied. This research explores how geospatial science, through the discipline of Geospatial Intelligence (GEOINT) can detect, monitor, and provide I &Wintelligence that prevents strategic surprise from hybrid threats. Specifically, this thesis applied a novel Strategic Intelligence Framework (SIF) to standard I & W intelligence practices to identify, analyze, and visualize PRC activities that carried hybrid threat characteristics within a U.S./Canadian Arctic and circumpolar study area. Through incorporating local spatial context via the Getis-Ord Gi* statistic, as well as the strength of the hybrid threat \signal," this case study successfully identified and mapped higher and lower threat regions using kernel density estimation (KDE) in the form of a Mesoscale Operational Situational Awareness Intelligence Composite (MOSAIC). The success of this case study shows that the SIF and MOSAIC are powerful tools for detecting, analyzing, and warning about the collective impact of hybrid threats.
dc.description.embargo2026-04-30
dc.identifier.urihttps://hdl.handle.net/1920/13018
dc.language.isoen
dc.subjectChina
dc.subjectArctic
dc.subjectIntelligence
dc.subjectGeospatial
dc.subjectGEOINT
dc.titleDetecting Great Power Competition Through Geospatial Analysis: A North American Arctic Case Study
dc.typeThesis
thesis.degree.disciplineGeoinformatics and Geospatial Intelligence
thesis.degree.grantorGeorge Mason University
thesis.degree.levelMaster's
thesis.degree.nameMaster of Science in Geoinformatics and Geospatial Intelligence

Files

License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.52 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

College of Science