Mapping Wild Leek through the Forest Canopy Using a UAV

Abstract

Abstract:Wild leek, an endangered plant species of Eastern North America, grows on forest floors and greens up to approximately three weeks before the trees it is typically found under, temporarily allowing it to be observed through the canopy by remote sensing instruments. This paper explores the accuracy with which wild leek can be mapped with a low-flying UAV. Nadir video imagery was obtained using a commercial UAV during the spring of 2017 in Gatineau Park, Quebec. Point clouds were generated from the video frames with the Structure-from-Motion framework, and a multiscale curvature classification was used to separate points on the ground, where wild leek grows, from above-ground points belonging to the forest canopy. Five-cm resolution orthomosaics were created from the ground points, and a threshold value of 0.350 for the green chromatic coordinate (GCC) was applied to delineate wild leek from wood, leaves, and other plants on the forest floor, with an F1-score of 0.69 and 0.76 for two different areas. The GCC index was most effective in delineating bigger patches, and therefore often misclassified patches smaller than 30 cm in diameter. Although short flight times and long data processing times are presently technical challenges to upscaling, the low cost and high accuracy of UAV imagery provides a promising method for monitoring the spatial distribution of this endangered species.

Identifying Species and Monitoring Understorey from UAS-Derived Data: A Literature Review and Future Directions

“…In total, we downloaded 131 articles that were then re-checked to assess their relevance. Ultimately, we only found 18 original-research articles that assessed both understorey vegetation and used high resolution remote sensing (Table 1; [1,18,19,22,[36][37][38][39][40][41][42][43][44][45][46][47][48][49]). We reviewed all of them.…”

“…Half of the articles conducted fieldwork (n = 10), and eight reported taking ground control measurements. Research by Ahmed et al [36] and Leduc and Knudby [40] reported the use of colour controls to calibrate imagery. The article by Weil et al [49] clumped most understorey species as 'herbaceous patches', but was kept because they identified several shrub species.…”

“…Cunliffe et al [22] used RGB data with a pixel size of 10 mm, successfully assessing vegetation structure through SfM methods (90% accuracy based on canopy height) to quantify biomass in heterogeneous semi-arid rangelands, and stated they were able to overcome detection limitations of smaller vegetation as associated with SfM precision levels identified in more complex habitats (e.g., forests). Leduc and Knudby [40] reported 76% accuracy when identifying a phenologically distinctive understorey 'spring ephemeral species', wild leek (Allium tricoccum), based on RGB imagery with a pixel size of 50 mm. Getzin et al [39] used RGB data with 70 mm resolution and correlated it with field work to successfully assess understorey diversity within canopy gaps of deciduous and deciduous/coniferous forests of Germany.…”

“…Nevertheless, sensors capturing only the RGB bands are sufficient in some instances. For example, Leduc and Knudby [40] reported successful monitoring of understorey species based on RGB data when easily distinguishable phenological characteristics were present, with an accuracy of 76%. Other successful studies were the result of spectral information that was complementary to other information, such as structural attributes derived from SfM.…”

Species and habitat mapping in two dimensions and beyond. Structure-from-Motion Multi-View Stereo photogrammetry for the Conservation Community

“…CloudCompare has proved a useful tool in a number of scientific studies, including those mapping wild leek (77), habitat suitability modelling for insect conservation (78), spatial ecology studies of coral and megabenthic invertebrates (79), and forest canopy ecology (80).…”