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PublisherThe University of Arizona.
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AbstractThe Remote Sensing Group (RSG) at the College of Optical Sciences of the University of Arizona implements a reflectance-based approach for vicariously calibrating remote sensors. This includes the automated radiometric data collection of the surface of Railroad Valley, Nevada (RRV) using four stationary Ground-Viewing Radiometers (GVRs). There are features such as cracks, pits, and small mounds on the surface of RRV. The ground instantaneous field-of-view (GIFOV) of a stationary GVR may contain more or less of these features than is indicative of the entire site. This thesis presents a design to increasing the spatial sampling via an automated motion control system that will translate the GVR over RRV a short distance. This will make for more accurate data collection in the automated reflectance-based calibration approach.
Degree ProgramGraduate College