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1 March 2008 Classification of Digital Photography for Measuring Productive Ground Cover
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Abstract

Productive ground cover (PGC) is often used as a measure of sward health and persistence. To measure PGC, a camera stand was constructed to provide diffuse lighting of grass swards for color digital photography; the photographs were classified into productive and nonproductive cover using Mahalanobis distance. The PGC measurement techniques were tested on a grazing experiment that used four forage types: Lakota prairie grass (Bromus catharticus Vahl.), Kentucky 31 endophyte (Neotyphodium coenophialum)-free tall fescue (Lolium arundinaceum [Schreb.] S. J. Darbyshire), Kentucky 31 endophyte-infected tall fescue, and Quantum (novel-endophyte) tall fescue. The accuracy of the PGC maps was assessed using a stratified subsample of 48 images, 12 from each of four productive cover classes (0%–39%, 40%–59%, 60%–79%, and 80%–100%). On each of these 48 images 100 random points were labeled by a single skilled interpreter. The PGC percentages thus derived had an 83.7% agreement with the PGC maps. However, the percentages derived from the PGC maps were not well correlated with the PGC percentages derived from either ocular estimation (r  =  0.22) or a simple digital point quadrat method (r  =  0.47). This experiment highlights the potential for semiautomated classification of ground-based digital photographs for estimating PGC, though further research (including more direct comparison with established field techniques) is warranted.

J. D. Rotz, A. O. Abaye, R. H. Wynne, E. B. Rayburn, G. Scaglia, and R. D. Phillips "Classification of Digital Photography for Measuring Productive Ground Cover," Rangeland Ecology and Management 61(2), 245-248, (1 March 2008). https://doi.org/10.2111/07-011.1
Received: 4 February 2007; Accepted: 1 September 2007; Published: 1 March 2008
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