Introducing close-range photogrammetry for characterizing forest understory plant diversity and surface fuel structure at fine scalesAuthor(s): Benjamin C. Bright; E. Louise Loudermilk; Scott M. Pokswinski; Andrew T. Hudak; Joseph J. O'Brien
Source: Canadian Journal of Remote Sensing. 42(5): 460-472.
Publication Series: Scientific Journal (JRNL)
Station: Rocky Mountain Research Station
Download Publication (692.0 KB)
Methods characterizing fine-scale fuels and plant diversity can advance understanding of plant-fire interactions across scales and help in efforts to monitor important ecosystems such as longleaf pine (Pinus palustris Mill.) forests of the southeastern United States. Here, we evaluate the utility of close-range photogrammetry for measuring fuels and plant diversity at fine scales (submeter) in a longleaf pine forest. We gathered point-intercept data of understory plants and fuels on nine 3-m2 plots at a 10-cm resolution. For these same plots, we used close-range photogrammetry to derive 3-dimensional (3D) point clouds representing understory plant height and color. Point clouds were summarized into distributional height and density metrics. We grouped 100 cm2 cells into fuel types, using cluster analysis. Comparison of photogrammetry heights with point-intercept measurements showed that photogrammetry points were weakly to moderately correlated to plant and fuel heights (r = 0.19-0.53). Mann-Whitney pairwise tests evaluating separability of fuel types, species, and plant types in terms of photogrammetry metrics were significant 44%, 41%, and 54% of the time, respectively. Overall accuracies using photogrammetry metrics to classify fuel types, species, and plant types were 44%, 39%, and 44%, respectively. This research introduces a new methodology for characterizing fine-scale 3D surface vegetation and fuels.
- You may send email to email@example.com to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationBright, Benjamin C.; Loudermilk, E. Louise; Pokswinski, Scott M.; Hudak, Andrew T.; O'Brien, Joseph J. 2016. Introducing close-range photogrammetry for characterizing forest understory plant diversity and surface fuel structure at fine scales. Canadian Journal of Remote Sensing. 42(5): 460-472.
Keywordsclose-range photogrammetry, forest understory, plant diversity, surface fuel structure, fine-scale fuels
- Application of ground-based LIDAR for fine-scale forest fuel modeling
- Ground-based LIDAR: a novel approach to quantify fine-scale fuelbed characteristics
- Understory fuel variation at the Carolina Sandhills National Wildlife Refuge: a description of chemical and physical properties
XML: View XML