A large-area trial of automated individual tree crown isolation and species classification on a 228-km2 site in central-eastern Ontario using 40 cm multispectral imagery gave insight into the complications and effectiveness of such approaches when applied to a complex mixed forest setting. Tree isolation was reasonably effective with few omissions and 77% of automated tree isolations (isols) were considered a good correspondence to ground truth delineations. There were issues with grouping several trees within 1 delineation, poor isols at the edges of stands and minor splitting (multiple isols per tree). Spectral characteristics of 18 species indicated considerable variability within species and overlap of signatures. To circumvent this, several spectral subclasses were created for certain species and the site was divided into broad and localized zones, which for ecological reasons had a reduced number of species. Mapping accuracy and classification accuracy of manually delineated trees for a main classification zone of 14 species, both typically ranged from 40% to 85%. For a simpler zone of 8 species, manual tree class accuracy averaged 76%. Possible improvements are discussed. Regardless of sophistication of techniques used, production of individual tree species maps in complex forests will require judicious use of human judgment and intervention.
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Leckie et al. (2017) studied this question.
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