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ARS Home » Northeast Area » Kearneysville, West Virginia » Appalachian Fruit Research Laboratory » Innovative Fruit Production, Improvement, and Protection » Research » Publications at this Location » Publication #252969

Title: Active spectral sensor evaluation under varying conditions

item Kim, James
item Glenn, David
item Park, Johnny - Purdue University
item Ngugi, Henry - Pennsylvania State University
item Lehman, Brian - Pennsylvania State University

Submitted to: Proceedings of the American Society of Agricultural and Biological Engineers International (ASABE)
Publication Type: Proceedings
Publication Acceptance Date: 4/25/2010
Publication Date: 5/17/2010
Citation: Kim, Y., Glenn, D.M., Park, J., Ngugi, H.K., Lehman, B.L. Active spectral sensor evaluation under varying conditions. Proceedings of the American Society of Agricultural and Biological Engineers International (ASABE). David L. Lawrence Convention Center, Pittsburgh, PA, June 20-23, 2010. ASABE Paper No. 10-09111.

Interpretive Summary:

Technical Abstract: Plant stress has been estimated by spectral signature using both passive and active sensors. As optical sensors measure reflected light from a target, changes in illumination characteristics critically affect sensor response. Active sensors are of benefit in minimizing uncontrolled illumination effects on optical sensors by producing their own illumination that is reflected from the target and measured by the detector. Although active sensors use modulated radiation that can be differentiated from ambient illumination, in order to validate data and increase the accuracy, sensor performance characteristics must be well understood and examined in different target conditions of plant leaves. The performance of an active NDVI sensor was evaluated to study the effect of: 1) partial canopy coverage, 2) target off-center, 3) standoff distance, 4) target surface tilting, 5) solar bidirectional effect, 6) temperature, and 7) diurnal radiation change. These evaluations provide a valid range of sensor measurement and a motivation to improve the measurement accuracy by using selective data that can be validated by a supplemental vision sensor.