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Optimal Remote Sensing with Small Unmanned Aircraft Systems and Risk Management

Creative Commons 'BY-NC' version 4.0 license

Over the past decade, the rapid rise of Unmanned Aircraft Systems (UASs) has blossomed into a new component of the aviation industry. Though regulations within the United States lagged, the promise of the ability of Small Unmanned Aircraft Systems (SUASs), or those UAS that weigh less than 55 lbs, has driven significant advances in small scale aviation technology. The dream of a small, low-cost aerial platform that can fly anywhere and keep humans safely away from the `dull, dangerous and dirty' jobs, has encouraged many to examine the possibilities of utilizing SUASin new and transformative ways, especially as a new tool in remote sensing. However, as with any new tool, there remains significant challenges in realizing the full potential of SUAS-based remote sensing. Within this dissertation, two specific challenges are addressed: validating the use of SUAS as a remote sensing platform and improving the safety and management of SUAS.

The use of SUAS in remote sensing is a relatively new challenge and while it has many similarities to other remote sensing platforms, the dynamic nature of its operation makes it unique. In this dissertation, a closer look at the methodology of using SUAS reveals that while many viewSUAS as an alternative to satellite imagery, this is an incomplete view and that the current common implementation introduces a new source of error that has significant implications on the reliability of the data collected. It can also be seen that a new approach to remote sensing with an \gls{SUAS} can be developed by addressing the spatial, spectral and temporal factors that can now be more finely adjusted with the use of SUAS.

However, to take the full advantage of the potential of SUAS, they must uphold the promise of improved safety. This is not a trivial challenge, especially for the integration into the National Airspace System (NAS) and for the safety management and oversight of diverse UAS operations. In this dissertation, the challenge of integrating SUAS in the NAS is addressed by presenting an analysis of enabling flight operations at night, developing a swarm safety management system for improving SUAS robustness, investigating the use of new technology on SUAS to improve air safety, and developing a novel framework to better understand human-SUAS interaction. Addressing the other side of safety, this dissertation discusses the struggle of large diverse organizations to balance acceptance, safety and oversight for UAS operations and the development of a novel implementation of a UAS Safety Management System.

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