Abstract
The invasive phytopathogen Phytophthora ramorum has caused extensive infection of larch forest across areas of the UK, particularly in Southwest England, South Wales and Southwest Scotland. At present, landscape level assessment of the disease in these areas is conducted manually by tree health surveyors during helicopter surveys. Airborne laser scanning (ALS), also known as LiDAR, has previously been applied to the segmentation of larch tree crowns infected by P. ramorum infection and the detection of insect pests in coniferous tree species. This study evaluates metrics from high-density discrete ALS point clouds (24points/m2) and canopy height models (CHMs) to identify individual trees infected with P. ramorum and to discriminate between four disease severity categories (NI: not infected, 1: light, 2: moderate, 3: heavy). The metrics derived from ALS point clouds include canopy cover, skewness, and bicentiles (B60, B70, B80 and B90) calculated using both a static (1m) and a variable (50% of tree height) cut-off height. Significant differences are found between all disease severity categories, except in the case of healthy individuals (NI) and those in the early stages of infection (category 1). In addition, fragmentation metrics are shown to identify the increased patchiness and intra-crown height irregularities of CHMs associated with individual trees subject to heavy infection (category 3) of P. ramorum. Classifications using a k-nearest neighbour (k-NN) classifier and ALS point cloud metrics to classify disease presence/absence and severity yielded overall accuracies of 72% and 65% respectively. The results indicate that ALS can be used to identify individual tree crowns subject to moderate and heavy P. ramorum infection in larch forests. This information demonstrates the potential applications of ALS for the development of a targeted phytosanitary approach for the management of P. ramorum.
Highlights
UK forestry has experienced notable introductions of several significant phytopathogens in recent decades (Brown et al, 2003; Brasier, 2008; Webber et al, 2008; Mitchell et al, 2014)
B20, B30 and B50 were removed from further analysis, in addition to B40 which was significant at the 90% confidence level
The research demonstrates the successful application of Airborne laser scanning (ALS) point cloud metrics to isolate individual tree crowns of larch subject to moderate and severe P. ramorum infection based on the impacts of the disease on individual tree crown canopy structure
Summary
UK forestry has experienced notable introductions of several significant phytopathogens in recent decades (Brown et al, 2003; Brasier, 2008; Webber et al, 2008; Mitchell et al, 2014). Current efforts to assess landscape-level patterns of P. ramorum infection and identify new outbreaks rely on visual aerial assessment conducted by tree-health surveyors during helicopter surveys. In this instance, foliar symptoms presented by infected larch aid the identification of P. ramorum. Despite the increased recognition of remote sensing as a tool for the assessment of forest health and disease, visual surveys continue to dominate in the operational management of pests and phytopathogens in the forestry sector (Hall et al, 2016; Lausch et al, 2017). Recognising the concerns of end-users is important for implementation of the results from scientific research into forestry management practise (Wulder et al, 2006)
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