Abstract

Stockpile volumes are monitored by their companies as the product (i.e., aggregate, soil) is moved in and out of the facilities to ensure minimal product loss. Companies are mandated to report product movement to the government to ensure that the aggregate and soil is going where it is supposed to go. Many tools are used to monitor stockpile volumes including truck scales (to weigh incoming and outgoing trucks), light detection and ranging (LiDAR), Global Navigation Satellite System (GNSS) equipment, and unmanned aerial vehicle (UAV) photogrammetry. These processes give a good estimate of stockpile volumes. Errors in these estimates typically come from transportation and natural degradation of the stockpile. Not much research has been done on the best practices when using UAV photogrammetry to find the volume of a stockpile. Most recent research is about specific situations for finding a stockpile volume and whether UAV photogrammetry is as good as traditional methods for finding stockpile's volume. This study focuses on the effect of the flight height, camera angle, and presence of ground control points (GCP) in processing on the final volume calculated. Six UAV flights were done for this study; three different flight heights and two different camera angles. Additionally, the UAV reconstructed models were run with and without the GCPs to give twelve reconstructed volumes to examine for statistically significant differences. A similar study was done by Tucci et. al\cite{Tucci2019} where they focused on only camera orientation and found that the camera orientation was not statistically significant. We found that the differences between if GCPs in processing or not and between each flight elevation was statistically insignificant. We found that the differences in camera orientation between nadir and oblique were statistically significant. These different results could be due to many variables including differences in the dataset, differences in the statistical analysis, or the difference in stockpile size. We recommend using a high flight elevation and oblique photos to develop an efficient, accurate model.

Degree

College and Department

Ira A. Fulton College of Engineering

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