Choosing a DIVA: a comparison of emerging digital imagery vegetation analysis techniques
Article first published online: 13 APR 2013
© 2013 International Association for Vegetation Science
Applied Vegetation Science
Volume 16, Issue 4, pages 552–560, October 2013
How to Cite
Jorgensen, C. F., Stutzman, R. J., Anderson, L. C., E. Decker, S., Powell, L. A., Schacht, W. H., Fontaine, J. J. (2013), Choosing a DIVA: a comparison of emerging digital imagery vegetation analysis techniques. Applied Vegetation Science, 16: 552–560. doi: 10.1111/avsc.12037
- Issue published online: 10 SEP 2013
- Article first published online: 13 APR 2013
- Manuscript Accepted: 12 MAR 2013
- Manuscript Received: 2 APR 2012
- U.S. Geological Survey National Climate Change and Wildlife Science Center
- Grassland vegetation structure;
- Estimating vegetative cover;
- Standing crop estimate;
- Vertical obstruction;
- Visual obstruction
What is the precision of five methods of measuring vegetation structure using ground-based digital imagery and processing techniques?
Lincoln, Nebraska, USA
Vertical herbaceous cover was recorded using digital imagery techniques at two distinct locations in a mixed-grass prairie. The precision of five ground-based digital imagery vegetation analysis (DIVA) methods for measuring vegetation structure was tested using a split-split plot analysis of covariance. Variability within each DIVA technique was estimated using coefficient of variation of mean percentage cover.
Vertical herbaceous cover estimates differed among DIVA techniques. Additionally, environmental conditions affected the vertical vegetation obstruction estimates for certain digital imagery methods, while other techniques were more adept at handling various conditions. Overall, percentage vegetation cover values differed among techniques, but the precision of four of the five techniques was consistently high.
DIVA procedures are sufficient for measuring various heights and densities of standing herbaceous cover. Moreover, digital imagery techniques can reduce measurement error associated with multiple observers' standing herbaceous cover estimates, allowing greater opportunity to detect patterns associated with vegetation structure.