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Species identification in Quebec, Canada, is usually performed with photo-interpretation at the stand level, and often results in a lack of precision which affects forest management. Very high spatial resolution imagery, such as WorldView-3 and Light Detection and Ranging have the potential to overcome this issue. The main objective of this study is to map 11 tree species at the tree level using an object-based approach. For modeling, 240 variables were derived from WorldView-3 with pixel-based and arithmetic feature calculation techniques. A global approach (11 species) was compared to a hierarchical approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were compared: support vector machine, classification and regression tree, random forest (RF), k-nearest neighbors, and linear discriminant analysis. Each model was assessed using 16-band or first 8-band derived variables, with the results indicating higher precision for the RF technique. Higher accuracies were found using 16-band instead of 8-band derived variables for the global approach (overall accuracy (OA): 75% vs. 71%, Kappa index of agreement (KIA): 0.72 vs. 0.67) and tree type level (OA: 99% vs. 97%, KIA: 0.97 vs. 0.95). For broadleaf individual species, higher accuracy was found using first 8-band derived variables (OA: 70% vs. 68%, KIA: 0.63 vs. 0.60). No distinction was found for individual conifer species (OA: 94%, KIA: 0.93). This paper demonstrates that a hierarchical classification approach gives better results for conifer species and that using an 8-band WorldView-3 instead of a 16-band is sufficient.

Sustainable management of boreal ecosystems involves the establishment of vigorous tree regeneration after harvest. However, two groups of understory plants influence regeneration success in eastern boreal Canada. Ericaceous shrubs are recognized to rapidly dominate susceptible boreal sites after harvest. Such dominance reduces recruitment and causes stagnant conifer growth, lasting decades on some sites. Additionally, peat accumulation due to Sphagnum growth after harvest forces the roots of regenerating conifers out of the relatively nutrient rich and warm mineral soil into the relatively nutrient poor and cool organic layer, with drastic effects on growth. Shifts from once productive black spruce forests to ericaceous heaths or paludified forests affect forest productivity and biodiversity. Under natural disturbance dynamics, fires severe enough to substantially reduce the organic layer thickness and affect ground cover species are required to establish a productive regeneration layer on such sites. We succinctly review how understory vegetation influences black spruce ecosystem dynamics in eastern boreal Canada, and present a multi-scale research model to understand, limit the loss and restore productive and diverse ecosystems in this region. Our model integrates knowledge of plant-level mechanisms in the development of silvicultural tools to sustain productivity. Fundamental knowledge is integrated at stand, landscape, regional and provincial levels to understand the distribution and dynamics of ericaceous shrubs and paludification processes and to support tactical and strategic forest management. The model can be adapted and applied to other natural resource management problems, in other biomes.