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Remote Sens. 2010, 2(1), 290-305; doi:10.3390/rs2010290

Acquisition of NIR-Green-Blue Digital Photographs from Unmanned Aircraft for Crop Monitoring

1
USDA-Agricultural Research Service, Hydrology and Remote Sensing Laboratory, Building 007 Room 104 BARC-West, 10300 Baltimore Avenue, Beltsville, MD 20705, USA
2
IntelliTech Microsystems, Inc., 2138 Priest Bridge Court, Suite 3, Crofton, MD 21114, USA
3
DSL Consulting, Inc., 7611 Kingfisher Court, Dexter, MI 48130, USA
*
Author to whom correspondence should be addressed.
Received: 8 November 2009 / Revised: 1 December 2009 / Accepted: 6 January 2010 / Published: 11 January 2010
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Abstract

Payload size and weight are critical factors for small Unmanned Aerial Vehicles (UAVs). Digital color-infrared photographs were acquired from a single 12-megapixel camera that did not have an internal hot-mirror filter and had a red-light-blocking filter in front of the lens, resulting in near-infrared (NIR), green and blue images. We tested the UAV-camera system over two variably-fertilized fields of winter wheat and found a good correlation between leaf area index and the green normalized difference vegetation index (GNDVI). The low cost and very-high spatial resolution associated with the camera-UAV system may provide important information for site-specific agriculture.
Keywords: unmanned aerial vehicle; UAV; green NDVI; leaf area index; Triticum aestivum; winter wheat unmanned aerial vehicle; UAV; green NDVI; leaf area index; Triticum aestivum; winter wheat
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Hunt, E.R., Jr.; Hively, W.D.; Fujikawa, S.J.; Linden, D.S.; Daughtry, C.S.T.; McCarty, G.W. Acquisition of NIR-Green-Blue Digital Photographs from Unmanned Aircraft for Crop Monitoring. Remote Sens. 2010, 2, 290-305.

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