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Technical Note: Classification of Digital Photography for Measuring Productive Ground Cover

J. D. Rotz, A. O. Abaye, R. H. Wynne, E. B. Rayburn, G. Scaglia and R. D. Phillips
Rangeland Ecology & Management
Vol. 61, No. 2 (Mar., 2008), pp. 245-248
Stable URL: http://www.jstor.org/stable/25146776
Page Count: 4
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Technical Note: 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. /// La cobertura basal (productiva PGC) a menudo es usada para medir la persistencia y salud de la pradera. Para medir la PGC se construyó un soporte para cámara para proveer una iluminación difusa de praderas de zacates para fotografías digitales a color. Las fotografías se clasificaron en cobertura productiva y no productiva usando la distancia de Mahalanobis. Las técnicas de cobertura basal productiva fueron probadas en un experimento de apacentamiento que uso cuatro tipos de forrajes: "Lakota prairie grass" (Bromus catharticus Vahl.), "Tall fescue Kentucky 31" (Lolium arundinaceum [Schreb.] S. J. Darbyshire) no endofito (Neotyphodium coenophialum), "Tall fescue Kentucky 31" endofito y "Tall fescue" Quantum (novel-endofito). La precisión de los mapas de PGC fue evaluada usando una submuestra etratificada de 48 imágenes, 12 de cada una de las cuatro clases de cobertura productiva clases (0%-39%, 40%-59%, 60%-79%, y 80%-100%). En cada una de las 48 imágenes un interpretador entrenado etiqueto aleatoriamente 100 puntos. Los porcentajes de PGC derivados de las imágenes tuvieron una concordancia de 83.7% con los mapas, sin embargo, los porcentajes derivados de los mapas de PGC no estuvieron bien correlacionados con los porcentajes de PGC derivados por estimación ocular (r = 0.22) o por el método de cuadrante simple de puntos digitales (r = 0.47). Este experimento resalta el potencial de la clasificación semi-automatizada de las fotografías digitales terrestres para estimar la PGC, aunque se requiere mas investigación (incluyendo una comparación más directa con las técnicas de campo establecidas).

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