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1 March 2005 Site-specific weed management: sensing requirements— what do we need to see?
Ralph B. Brown, Scott D. Noble
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Automated detection and identification of weeds in crop fields is the greatest obstacle to development of practical site-specific weed management systems. Research progress is summarized for two different approaches to the problem, remote sensing weed mapping and ground-based detection using digital cameras or nonimaging sensors. The general spectral and spatial limitations reported for each type of weed identification system are reviewed. Airborne remote sensing has been successful for detection of distinct weed patches when the patches are dense and uniform and have unique spectral characteristics. Identification of weeds is hampered by spectral mixing in the relatively large pixels (typically larger than 1 by 1 m) and will not be possible from imagery where weed seedlings are sparsely distributed among crop plants. The use of multispectral imaging sensors such as color digital cameras on a ground-based mobile platform shows more promise for weed identification in field crops. Spectral features plus spatial features such as leaf shape and texture and plant organization may be extracted from these images. However, there is a need for research in areas such as artificial lighting, spectral band requirements, image processing, multiple spatial resolution systems, and multiperspective images.

Ralph B. Brown and Scott D. Noble "Site-specific weed management: sensing requirements— what do we need to see?," Weed Science 53(2), 252-258, (1 March 2005).
Received: 18 March 2004; Accepted: 1 December 2004; Published: 1 March 2005
Machine vision
remote sensing
spectral reflectance
weed identification
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