Establishing an evidence-based foundation for the integration of emerging technologies in 3D GIScience

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Thesis type
(Thesis) Ph.D.
Date created
Geography is increasingly reliant on modern technology and rapid technological advancements have inspired novel uses of these technologies for geospatial applications. Geographic Information Systems (GISs) themselves, the backbone of contemporary geospatial analyses, were once considered a novel technology in search of an application, and it was not until Geographic Information Science (GIScience) established the science of GIS that GIS earned its legitimacy as a scientific tool. In many ways, emerging geospatial technologies (EGTs), or technologies that have only recently been adopted for geospatial applications (i.e., data capture, analysis, or delivery), are experiencing the same challenges as early GISs. EGTs such as Structure from Motion (SfM) and Extended Reality (XR) have experienced increased adoption in the geospatial realm despite uncertainty surrounding their use and usefulness as spatially rigorous 3D GIScience tools. There is a need for the 3D GIScience that supports the use of these EGTs as legitimate scientific tools. In this dissertation, five manuscripts are presented: 1) a novel SfM workflow and a series of performance benchmarks quantifying the impact that camera, camera settings, lighting, and capture strategy have on 3D data accuracy; 2) an assessment of a SfM workflow in a simulated temperate benthic environment and the impact that underwater camera equipment has on 3D data accuracy; 3) an evaluation of temperate marine SfM performance and the opportunity for XR based 3D data visualizations of complex morphology; 4) a discussion on the design and development of immersive virtual environments for geospatial visual analytics and the interpretation of 3D spatial data sets, and; 5) an immersive mental rotations test to evaluate the impact that virtual reality based visualizations and 3D virtual environments have on mental rotation task performance. These five manuscripts explore and evaluate SfM and XR as EGTs for 3D data capture, visualization, and analysis. This research endeavors to strengthen the empirical foundation supporting the use of these EGTs as legitimate geospatial technologies for 3D GIScience and geospatial visual analytics.
232 pages.
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Supervisor or Senior Supervisor
Thesis advisor: Hedley, Nick
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