Browsing by Author "Hower, Madeline"

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    Drone Technology and University Public Safety Program Proposal
    Hower, Madeline; Makwana, Sunny; Kerrick, Cason (2020-12-08)
    This report is an initial program proposal for drone technology use for university public safety. Three different areas of focus are addressed in this report by the research team. The three focuses will include an extensive case study of similar programs adopted in other locations, with an analysis of their successes and failures, a proposed survey to be sent to Virginia Tech students on drone technology and the use of UAVs on campus and a CANVAS module outline used to inform Virginia Tech students of the campus drone guidelines, and a description of current Virginia Tech policies related to the proposed program and their challenges and needed adoptions. This product is a learning artifact from the Fall 2020 semester of the Honors and UAP SuperStudio courses (UH-4504, UAP-4914, and UH-4514). Course instructors: Joanie Banks-Hunt, Ralph Hall, Nikki Lewis, Amy Showalter, Zack Underwood, Anne-Lise Velez, and Daron Williams
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    The Influence of Flight Speed, Image Overlap, and Lighting Conditions on the Spatial Accuracy and Development Time of Low-Cost UAS Imaging
    Hower, Madeline (Virginia Tech, 2024)
    Widespread emerging UAV technology has resulted in an increased use of drones across a variety of fields to complete mapping and surveying evaluations. However, accessible guidelines providing information on the effects parameter choices and environmental considerations have on orthomosaic quality and accuracy do not exist. To improve the understanding of the various influences on mapping results, this study evaluates how image overlap ratio, mapping speed, and lighting conditions affect spatial accuracy and development time for resulting orthomosaic images. This evaluation was done by conducting mapping missions with several parameter variations over a homogeneous area and a non-homogeneous area. The accuracy was assessed by calculating the root mean square error (RMSE). The results suggest that effects of mapping parameters differ between homogeneous and non-homogeneous areas. For a homogeneous location, the most accurate conditions were obtained by conducting mapping on a clear weather day, with a 60/80 overlap, at a mapping speed of 3 m/s. For the non-homogeneous location, the most accurate conditions were conducting mapping on a cloudy weather day, with a 70/80 overlap, at a mapping speed of 5m/s. A correlation was also found between lighting conditions and image development time and between image overlap and image development time, where clear day weather resulted in a lower processing time and reducing front overlap had the greatest reduction in processing time.