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United States Department of Agriculture

Agricultural Research Service


item Hunt, Earle - Ray
item Walthall, Charles
item Daughtry, Craig
item Fujikawa, Stephen
item Yoel, David
item Khorrami, Farshad
item Tranchitella, Michael

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 6/21/2005
Publication Date: 10/5/2005
Citation: Hunt, E.R., Walthall, C.L., Daughtry, C.S., Fujikawa, S.J., Yoel, D., Khorrami, F., Tranchitella, M. 2005. High resolution multispectral digital photography using unmanned airborne vehicles [abstract]. 20th Biennial workshop on Areal Photography, Videography, and High Resolution Digital Imagery for Resource Assessment. 2005 CDROM.

Interpretive Summary:

Technical Abstract: An Unmanned Airborne Vehicle (UAV) from IntelliTech Microsystems, Inc. was fitted with two down-looking digital cameras, an up-looking quantum sensor, and computer controls based on GPS position. The internal filters of the cameras were removed and external narrow-band filters at 490 nm, 550 nm, 610 nm, 675 nm, and 800 nm were fitted onto the cameras. Colored tarpaulins were used to calibrate the images; there were large differences in digital number (DN) for a given tarpaulin. When incident radiation was accounted for using the quantum sensor, the imagery matched the tarpaulin reflectances. For soybean, alfalfa and corn grown at the Beltsville Agricultural Research Center, dry biomass from zero to 120 g m-2 was linearly correlated to vegetation indices based on a visible band and the 800 nm band, but for biomass greater than 150 g m-2 in corn and soybean, these indices were saturated. UAV’s can be launched in narrow windows of good weather, fly large fields in preplanned patterns, and deliver the data rapidly to the user at lower cost, making these data particularly suitable for precision agriculture.

Last Modified: 10/18/2017
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