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Dissertation/Thesis Abstract

The Development of a Multispectral Remote Sensing sUAS Using Commercial Band Pass Filters in Support of Muscadinia Rotundafolia Precision Viticulture
by Thompson, Grant Bradford, Jr., M.S., College of Charleston, 2020, 95; 28314209
Abstract (Summary)

The Santee Cooper Geospatial Information Sciences (GIS) Laboratory (SCGIS) is the primary academic GIS research organization providing support to College of Charleston (CofC) and the Charleston community. In 2016 SCGIS acquired a DJI Phantom 4 small unmanned airborne system (sUAS) to enhance its remote sensing capabilities. To further develop native sUAS capacity, I undertook a project to validate the use of Thor Labs band-pass filters in the development and deployment of a low-cost multispectral sUAS remote sensing platform for use in precision viticulture research. I constructed and tested a mounting system for the filters and conducted investigatory missions during the 2019 and 2020 growing seasons. I used commercially available geospatial information systems (GIS) applications to develop visible-light vegetation index products that were established measures of plant health, little of which had been conducted in North American vineyards. In this study, I compare the data and products derived from filtered and unfiltered imagery to assess similarity and relative accuracy. There were statistically significant variances between the paired sets of data, indicating that the light reflectances detected by the camera could not be considered the same. The data and products derived from unfiltered imagery showed greater fidelity, data normality, and finer pixel-scale variation than those derived from filtered imagery. This study shows that band pass filters may have application in sUAS-based remote sensing, but the filters used were not suitable to this type of research. However, the high quality of the unfiltered imagery and products demonstrate that sUAS-based remote sensing is highly applicable to precision viticulture research in the United States.

Indexing (document details)
Advisor: Levine, Norman
Commitee: Chadwick, D. J., Watson, Annette, Siegel, Donald
School: College of Charleston
Department: Environmental Studies
School Location: United States -- South Carolina
Source: MAI 82/8(E), Masters Abstracts International
Source Type: DISSERTATION
Subjects: Remote sensing, Agriculture, Sustainability, Optics, Computer science, Artificial intelligence, Geographic information science
Keywords: Drone, Precision agriculture, Precision viticulture, Vegetation index, Visible light, Small unmanned airborne system (sUAS)
Publication Number: 28314209
ISBN: 9798569967339
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