Inside Unmanned Systems

MAY 2015

Inside Unmanned Systems provides actionable business intelligence to decision-makers and influencers operating within the global UAS community. Features include analysis of key technologies, policy/regulatory developments and new product design.

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60 unmanned systems inside Spring 2015 AIR PRECISION AGRICULTURE A griculture is projected to be one of the largest, if not the largest, commercial applications of Unmanned Aircraft System (UAS) in the United States. The avail- ability of small, affordable, and easy to operate UAS are driving a surge in interest. Some of the key technologies enabling small UAS to be part of the precision agriculture revolution are: the development of miniaturized imag- ing sensors for low altitude aerial sensing of specific wavelengths of light that relate to crop health, the proliferation of small and affordable unmanned aircraft that contain GPS enabled autopilots, and advances in image processing and data management along with ever more IT infrastructure out at the farm. UAS in the form of robotic helicopters have been used in Japanese agriculture for 20 years and have achieved widespread adoption for precision spraying of rice fields. Over the past decade RTK GPS used in precision planting, auto driving tractors, and variable rate sprayers by Hamid Mokhtarzadeh, Ian MacRae, Robert Koch, Zach Marston, Terrance Hurley, Demoz Gebre- Egziabher, Todd Colten UAS TARGETING AGRICULTURE PRECISION have become commonplace on most farming operations in the United States. Use of aerial imagery captured from small UAS seems likely to follow a similar adoption trend. Aerial imagery from UAS can be used to help find areas in a field where plants might be under stress and therefore are not growing to their full economic potential. Small UAS are particularly suited to on-demand data collec- tion of this sort. The overall approach is to use a small UAS carrying a specialized lightweight camera to take high resolution pictures of the crops in the red and near-infrared spectrum. These spec- trums can be used to obtain a relative mea- sure of crop health through an image process- ing algorithm; one example of which is called the Normalized Difference Vegetation Index (NDVI). These specialized cameras are called multispectral cameras. Other wavelengths of reflected light might be captured as well de- pending on the exact camera used. The small

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