# Mapping Wild Leek through the Forest Canopy Using a UAV
## 4 Discussion  
Accurate information on the spatial extent of indicator species is important for the effective management of ecosystems. This study evaluates the feasibility of mapping wild leek in Gatineau Park using the GCC index derived from UAV-based imagery in combination with SfM techniques. The multiscale curvature algorithm implemented in MCC-LIDAR visually appeared effective in separating ground returns from non-ground returns in our study areas (Figure 4). MCC-LIDAR is intended for classifying LIDAR returns in densely forested complex terrains [49; 61; 62], but also performed well on the SfM-generated point clouds, regardless of the elevation changes and variations of the terrain. Others have found that MCC-LIDAR retained ground features like rock outcroppings that other algorithms removed, but was unable to filter vegetation features that created a plainer surface [63]. Wild leek can sometimes be found in more open areas, although we did not encounter this in Gatineau Park. For such cases, prior knowledge of the terrain should be considered and more detailed tests should be conducted before selecting an algorithm for the elimination of non-ground points [63; 64]. The lack of coniferous trees at our two sites is important to note because these are often misclassified when using MCC-LIDAR [48; 63]. In Gatineau Park, wild leek is not typically found under a coniferous canopy, but this may not be the case elsewhere. An important constraint for the ground vs. non-ground classification process using MCC-LIDAR is the size limit of the input data (\(\sim\)25 million points) and the long processing time [49; 65]. To apply this technique practically on a larger scale, it will be necessary to shorten the processing time and allow a larger point cloud to be processed. Further investigation will be needed to assess the possibility of using other ground filtering algorithms for large areas that would yield results comparable to MCC. The accuracy assessment demonstrated that a GCC threshold calibrated for one area can be applied to another area and used to map wild leek with a good accuracy (F1 = 0.76), which bodes well for wider application of the method in Gatineau Park. Although we did not specifically test  
Figure 6: Comparison of (**a**) 1-cm resolution orthomosaics produced from a smartphone and used for validation, (**b**) 5-cm resolution orthomosaics produced from UAV video frames, and (**c**) classification of wild leek (blue) based on the GCC threshold, for four corners of Area 2.  
the influence of environmental factors on this threshold transferability, visual inspection did not suggest that common factors such as terrain (slope vs. flat) affected it. In fact, the accuracy assessment may underestimate the true classification accuracy. Despite our best efforts, the geometric overlap between the orthomosaics used for classification and validation was visibly imperfect, and several validation data points appear to have been'misclassified' for this reason. We also noticed that very small patches of wild leek produced low GCC values and, as a result, were excluded from the wild leek class. This occurred mostly for patches that were less than 30 cm wide, and contributes to lowering the classification accuracy. The GCC worked best when wild leek patches, big or small, are well separated. For instance, in corner 1 of Area 2 (leftmost column in Figure 6), the GCC worked particularly well to delineate small distant wild leek patches that were surrounded by small patches of other spring ephemerals. In contrast, in locations where wild leek was more abundant and where patches occurred closer to each other (i.e., Area 1, corner imagery not shown), gaps between patches were often misclassified as wild leek, which might be responsible for a lower classification accuracy (0.69). The effectiveness of using a simple greenness threshold to identify an individual species is dependent on environmental context, and would not work in the presence of other understory species with similar phenology and greenness.