Steven Hard

Date of Graduation

2018

Document Type

Thesis

Degree Type

MS

College

Statler College of Engineering and Mineral Resources

Department

Lane Department of Computer Science and Electrical Engineering

Committee Chair

Powsiri Klinkhachorn

Committee Co-Chair

Roy S Nutter

Committee Member

Mario G Perhinschi

Abstract

The focus of this research has been the design and fabrication of a Normalized Difference Vegetation Index (NDVI) payload configuration. This unique payload employs low-cost commercial off-the-shelf (COTS) hardware and equipment to assess photosynthetic activity and vegetation health through remote sensing on Cubesat or Unmanned Aerial Vehicle (UAV) platforms. The proposed NDVI imaging payload is comprised of three main subsystems: an electrical system, a software system, and a hardware system. The electrical system includes a custom designed printed circuit board (PCB), a single cell 3.7 V lithium-polymer battery, voltage regulator circuitry components, and wiring harnesses and connectors. The software system employs a master and slave system that communicates through general purpose input/output (GPIO) pin responses. Raspberry Pi Zero computer boards serve as the central processing units (CPUs) of the hardware subsystem, which also consists of the Pi-Cam standard red/green/blue (RGB) and Pi No-IR near-infrared (NIR) camera modules. A PCB was designed to be compatible with the Cubesat standard and lightweight component selections make it a desirable option for UAV flights. Open-source GIMP image processing software was used to analyze results from ground-based testing and flight testing on a UAV and general aviation (GA) aircraft at various altitudes to validate proof of concept. Raw NDVI and NDVI color map images were created from GIMP post-processing. Analysis of the results suggests that the angle of incidence of the sun with respect to the view angle of the imaging payload is a significant factor in the resulting NDVI values. Terrain also appeared to have an effect on the results where shadows were cast from the sun at low angles of incidence. Therefore, in the northern hemisphere it is recommended that image collection is performed roughly within the hours of 10 AM and 2 PM between the vernal and autumnal equinoxes to ensure a solar altitude of at least 35°. For best results, it has been verified that image data should be collected at the local time of maximum solar altitude for a particular date and location of interest (typically around noon). The information gather by this research can be used by scientists and technologist to potentially provide a means of enhancing their research and further developing technologies of UAV applications and space-based systems.

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