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Research Project:
QUANTIFYING AND MONITORING NUTRIENT CYCLING, CARBON DYNAMICS AND SOIL PRODUCTIVITY AT FIELD, WATERSHED AND REGIONAL SCALES
Location: Hydrology and Remote Sensing Laboratory
Title: NIR-green-blue high-resolution digital images for assessement of winter cover crop biomass
Authors
Submitted to: GIScience and Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 11, 2011
Publication Date: March 15, 2011
Citation: Hunt, E.R., Hively, W.D., McCarty, G.W., Daughtry, C.S., Forrestal, P., Carr, J.L., Allen, N.F., Fox-Rabinovitz, J., Miller, C. 2011. NIR-green-blue high-resolution digital images for assessement of winter cover crop biomass. GIScience and Remote Sensing. 48(1):86-89.
Interpretive Summary: Many small unmanned aerial systems use true-color digital cameras for remote sensing. For some cameras, only the red channel is sensitive to near-infrared (NIR) light; we attached a custom red-blocking filter to a digital camera to obtain NIR-green-blue digital images. One advantage of this low-cost system is that images can be inspected directly from the camera. This camera was flown in a Piper Cub aircraft for estimating biomass of wheat and barley planted as winter cover crops. There was much greater variation in biomass within plots than between plots, so correlations with plot averages were not high. Current needs are to develop better calibration methods so camera sensors can be used for precision agriculture.
Technical Abstract:
Many small unmanned aerial systems use true-color digital cameras for remote sensing. For some cameras, only the red channel is sensitive to near-infrared (NIR) light; we attached a custom red-blocking filter to a digital camera to obtain NIR-green-blue digital images. One advantage of this low-cost system is that images can be inspected directly from the camera. This camera was flown in a Piper Cub aircraft for estimating biomass of wheat and barley planted as winter cover crops. There was much greater variation in biomass within plots than among plots, so correlations with plot averages were not high. Current needs are to develop better calibration methods so camera sensors can be used for precision agriculture.
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