In recent years, significant advancements have been made in both sensor technology and small Unmanned Aircraft Systems (sUAS). Improved sensor technology has provided users with cheaper, lighter, and higher resolution imaging tools, while new sUAS platforms have become cheaper, more stable and easier to navigate both manually and programmatically. These enhancements have provided remote sensing solutions for both commercial and research applications that were previously unachievable. However, this has provided non-scientific practitioners with access to technology and techniques previously only available to remote sensing professionals, sometimes leading to improper diagnoses and results. The work accomplished in this dissertation demonstrates the impact of proper calibration and reflectance correction on the radiometric quality of sUAS imagery.
The first part of this research conducts an in-depth investigation into a proposed technique for radiance-to-reflectance conversion. Previous techniques utilized reflectance conversion panels in-scene, which, while providing accurate results, required extensive time in the field to position the panels as well as measure them. We have positioned sensors on board the sUAS to record the downwelling irradiance which then can be used to produce reflectance imagery without the use of these reflectance conversion panels.
The second part of this research characterizes and calibrates a MicaSense RedEdge-3, a multispectral imaging sensor. This particular sensor comes pre-loaded with metadata values, which are never recalibrated, for dark level bias, vignette and row-gradient correction and radiometric calibration. This characterization and calibration studies were accomplished to demonstrate the importance of recalibration of any sensors over a period of time. In addition, an error propagation was performed to detect the highest contributors of error in the production of radiance and reflectance imagery.
Finally, a study of the inherent reflectance variability of vegetation was performed. In other words, this study attempts to determine how accurate the digital count to radiance calibration and the radiance to reflectance conversion has to be. Can we lower our accuracy standards for radiance and reflectance imagery, because the target itself is too variable to measure? For this study, six Coneflower plants were analyzed, as a surrogate for other cash crops, under different illumination conditions, at different times of the day, and at different ground sample distances (GSDs).
Library of Congress Subject Headings
Remote-sensing images--Evaluation; Drone aircraft; Radiation--Measurement
Imaging Science (Ph.D.)
Department, Program, or Center
Chester F. Carlson Center for Imaging Science (COS)
Mamaghani, Baabak G., "An Analysis of the Radiometric Quality of Small Unmanned Aircraft System Imagery" (2019). Thesis. Rochester Institute of Technology. Accessed from
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