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Title: IMAGE ANALYSIS COMPARED WITH OTHER METHODS FOR MEASURING GROUND COVER

Author
item Booth, D
item Cox, Samuel
item FIFIELD, CHARLES - USDI-BLM
item PHILLIPS, M - USDI-BLM
item WILLIAMSON, N - NPS

Submitted to: Arid Land Research and Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/26/2004
Publication Date: 4/5/2005
Citation: Booth, D.T., Cox, S.E., Fifield, C., Phillips, M., Williamson, N. 2005. Image analysis compared with other methods for measuring ground cover. Arid Land Research and Management. 19:91-100.

Interpretive Summary: Measurements of bare ground / ground cover continue to be a standard part of rangeland environmental assessments, but conventional measurement methods are labor intensive. The measurement of bare ground from digital images has the potential to reduce the labor requirement. We compared data and data-collection time for digital image collection analysis with 3 more conventional methods. We found there was low agreement in plot-to-plot comparisons, but that the results were about equal when averaged over 20 or more photographs. We conclude that image analysis of large numbers of photographic samples produce average values not different from values resulting from more conventional methods - and that image analysis is a superior method for detecting relative change since it encourages greater data collection, reduces human bias, and provides a permanent record in images that can be retained for future examination.

Technical Abstract: Ground cover is a key indicator of rangeland health, but conventional methods for measuring ground cover are labor intensive. Analysis of digital images has the potential to reduce ground-cover-measurement labor requirements. We compared cover measurements from image analyses with those derived from a laser point frame, and from 2 transect methods. We found there was low agreement in plot-to-plot comparisons, but that results were usually not different when averaged over a large number of plots or transects. We conclude that image analysis of large numbers of samples (images) produce mean values not different from conventional field methods, and, that image analysis is a superior choice for detecting relative change since it facilitates greater data collection, reduces human bias by limiting human judgments, and provides a permanent record in images that can be retained for future scrutiny.