Introducing Close-Range Photogrammetry for Characterizing Forest Understory Plant Diversity and Surface Fuel Structure at Fine Scales

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-m(2) 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 100cm(2) 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.