Classification of Digital Photography for Measuring Productive Ground Cover
dc.contributor.author | Rotz, J. D. | |
dc.contributor.author | Abaye, A. O. | |
dc.contributor.author | Wynne, R. H. | |
dc.contributor.author | Rayburn, E. B. | |
dc.contributor.author | Scaglia, G. | |
dc.contributor.author | Phillips, R. D. | |
dc.date.accessioned | 2020-09-05T07:11:30Z | |
dc.date.available | 2020-09-05T07:11:30Z | |
dc.date.issued | 2008-03-01 | |
dc.identifier.citation | Rotz, J. D., Abaye, A. O., Wynne, R. H., Rayburn, E. B., Scaglia, G., & Phillips, R. D. (2008). Classification of digital photography for measuring productive ground cover. Rangeland Ecology & Management, 61(2), 245-248. | |
dc.identifier.issn | 0022-409X | |
dc.identifier.doi | 10.2111/07-011.1 | |
dc.identifier.uri | http://hdl.handle.net/10150/642948 | |
dc.description.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. | |
dc.language.iso | en | |
dc.publisher | Society for Range Management | |
dc.relation.url | https://rangelands.org/ | |
dc.rights | Copyright © Society for Range Management. | |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
dc.subject | camera stand | |
dc.subject | digital aerial photography | |
dc.subject | image classification | |
dc.subject | grazing | |
dc.subject | pastures | |
dc.subject | prairie grass | |
dc.subject | tall fescue | |
dc.title | Classification of Digital Photography for Measuring Productive Ground Cover | |
dc.type | text | |
dc.type | Article | |
dc.identifier.journal | Rangeland Ecology & Management | |
dc.description.collectioninformation | The Rangeland Ecology & Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact lbry-journals@email.arizona.edu for further information. | |
dc.eprint.version | Final published version | |
dc.description.admin-note | Migrated from OJS platform August 2020 | |
dc.source.volume | 61 | |
dc.source.issue | 2 | |
dc.source.beginpage | 245-248 | |
refterms.dateFOA | 2020-09-05T07:11:30Z |