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Benchmarking tree species classification from proximally-sensed laser scanning data: introducing the FOR-species20K dataset

The FOR-species20K dataset, available at https://zenodo.org/records/13255198, is a key resource for developing and benchmarking DL models for tree species classification using laser scanning data, providing a foundation for future advancements in the field.
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Benchmarking tree species classification from proximally sensed laser scanning data: Introducing the FOR‐species20K dataset

The FOR‐species20K benchmark dataset, consisting of individual tree point clouds captured using proximally sensed laser scanning data from terrestrial (TLS), mobile (MLS) and drone laser scanning (ULS), is compiled and seven leading DL models for individual tree species classification are benchmarked, including both point cloud and multi‐view 2D‐based methods.
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Performance assessment of two plotless sampling methods for density estimation applied to some Alpine forests of northeastern Italy

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