Journal
ENVIRONMENTAL AND EXPERIMENTAL BOTANY
Volume 65, Issue 2-3, Pages 238-244Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.envexpbot.2008.09.013
Keywords
Digital camera; Green-up; Robotic; HSL color space
Categories
Funding
- National Science Foundation [0120778]
- Direct For Computer & Info Scie & Enginr [0120778] Funding Source: National Science Foundation
- Division of Computing and Communication Foundations [0120778] Funding Source: National Science Foundation
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Plant phenology relates strongly to primary productivity and the energy that enters into ecological food webs, and thus is vital in understanding ecosystem function and the effects of climate and climate change. The manual collection of phenological data is labor-intensive and not easily scalable, thus the ability to quantify leaf flush and other parameters at many locations requires innovative new methodologies such as the use of visible light digital cameras. improved imaging performance was obtained by using a cabled, mobile camera system that allowed a repeated image census of branches of Rhododendron occidentale in the understory along a 30 m transect during leaf flush. Automatic division of acquired images into areas of interest (leaves) and background for calculating leaf area was accomplished by thresholding images in different color spaces. Transformation of the color space into the hue, saturation, and luminance (HSL) color space before thresholding resulted in a mean RMS error of 21.2 cm(2) compared to hand-counts of leaf area. Thresholding in the native red, green, and blue (RGB) color space to isolate leaves resulted in a larger error, as did using algebraic combinations of the color components or color ratios. Relating physiological function to images, as for sap flow for branches of R. occidentale, indicates that the greening and calculated leaf area of a species as detected by imagers requires additional meteorological sensor data for interpretation. (C) 2008 Elsevier B.V. All rights reserved.
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