7 citations · 7 across the 3 of their papers we have counts for
4 papers
Multispectral airborne laser scanning dataset for tree species classification: MS-ALS-SPECIES
Matti Hyyppä, Klaara Salolahti, Eric Hyyppä +9
The shift from stand-level to individual-tree-level forest assessments supports improved species mapping and biodiversity monitoring, particularly in boreal ecosystems where tree s…
Learning Image-based Tree Crown Segmentation from Enhanced Lidar-based Pseudo-labels
Julius Pesonen, Stefan Rua, Josef Taher +3
Mapping individual tree crowns is essential for tasks such as maintaining urban tree inventories and monitoring forest health, which help us understand and care for our environment…
Benchmarking individual tree segmentation using multispectral airborne laser scanning data: the FGI-EMIT dataset
Lassi Ruoppa, Tarmo Hietala, Verneri Seppänen +6
Individual tree segmentation (ITS) from LiDAR point clouds is fundamental for applications such as forest inventory, carbon monitoring and biodiversity assessment. Traditionally, I…
Multispectral airborne laser scanning for tree species classification: a benchmark of machine learning and deep learning algorithms
Josef Taher, Eric Hyyppä, Matti Hyyppä +46
Climate-smart and biodiversity-preserving forestry demands precise information on forest resources, extending to the individual tree level. Multispectral airborne laser scanning (A…