Date of Award:
Master of Science (MS)
Electrical and Computer Engineering
This work concentrates on the topic of remote sensing using a multispectral imag-ing system for water management and agriculture applications. The platform, which is alight-weight inexpensive runway-free unmanned aerial vehicle (UAV), namely, AggieAir, ispresented initially. A major portion of this work focuses on the development of a light-weight multispectral imager payload for the AggieAir platform, called GhostFoto. Theimager is band-recongurable, covering both visual red, green, and blue (RGB) and nearinfrared (NIR) spectrum, and interfaced with UAV on-board computer. The developmentof the image processing techniques, which are based on the collected multispectral aerialimages, is also presented in this work. One application is to perform fully autonomous rivertracking for applications such as river water management. Simulation based on aerial mul-tispectral images is done to demonstrate the feasibility of the developed algorithm. Othereort is made to create a systematic method to generate normalized difference vegetationindex (NDVI) using the airborne imagery. The GhostFoto multispectral imaging systembased on AggieAir architecture is proven to be an innovative and useful tool.
Han, Yiding, "An Autonomous Unmanned Aerial Vehicle-Based Imagery System Development and Remote Sensing Images Classification for Agricultural Applications" (2009). All Graduate Theses and Dissertations. 513.
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