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Remote sensing with unmanned aircraft systems for precision agriculture applications

The Federal Aviation Administration is revising regulations for using unmanned aircraft systems (UAS) in the national airspace. An important potential application of UAS may be as a remote-sensing platform for precision agriculture, but simply down-scaling remote sensing methodologies developed using satellite and high-altitude aircraft platforms will create problems for data analysis. We simulated UAS image acquisition using both commercial and modified digital cameras mounted on an extension pole. The modified digital camera did not have an internal hot-mirror filter and had a red-cut filter to produce blue, green and near-infrared digital images. Green Normalized Difference Vegetation Indices from the modified camera was best for biomass and cover, whereas the blue, green and red digital cameras were better for estimating leaf chlorophyll content and nitrogen deficiency symptoms. The very small pixel sizes possible with UAS provide considerable information, but spectral methods of analysis are inadequate to extract the information.