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Weed–Crop Discrimination Using Remote Sensing: A Detached Leaf Experiment

Published online by Cambridge University Press:  20 January 2017

Anne M. Smith  and
Robert E. Blackshaw
Anne M. Smith*
Affiliation:
Agriculture and Agri-Food Canada, Research Centre, 5403 1st Avenue South, Lethbridge, AB, T1J 4B1 Canada
Robert E. Blackshaw
Affiliation:
Agriculture and Agri-Food Canada, Research Centre, 5403 1st Avenue South, Lethbridge, AB, T1J 4B1 Canada
*
Corresponding author's E-mail: smitha@agr.gc.ca
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Abstract

Mapping weed infestations in an annual crop has implications not only for site-specific herbicide applications but also for planning future management strategies and understanding weed ecology. A controlled laboratory experiment, involving detached leaves, was conducted to investigate the potential to discriminate two crop and five weed species using hyperspectral and multispectral remote sensing. Stepwise discriminant function analyses showed that reflectance in the visible and “red-edge” regions of the spectrum were consistently required for species discrimination. The seven species were correctly identified 90 and 89% of the time using the hyperspectral and multispectral data, respectively, and the classification rules derived from discriminant function analyses. Errant species prediction with the hyperspectral data resulted in a grass being predicted as a grass and a broadleaf as a broadleaf. However, for multispectral data, incorrect classifications were more serious because errant predictions sometimes resulted in a grass being classified as a broadleaf and vice-versa. Further studies using plants at a variety of growth stages, from a variety of environments, and at the canopy level are warranted.

Keywords

Hyperspectralleaf reflectancemultispectralAmaranthus retroflexusAvena fatuaBrassica kaberChenopodium albumSetaria viridisBrassica napusTriticum aestivumAMAREAVEFACHEALSETVISINARSMA, spectral mixture analysis

Information

Type
Research
Information
Weed Technology , Volume 17 , Issue 4 , December 2003 , pp. 811 - 820
Copyright
Copyright © Weed Science Society of America 

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