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 biodiversity mapping, particularly in boreal ecosystems where tree species like aspen (Popu…
Riverine Land Cover Mapping through Semantic Segmentation of Multispectral Point Clouds
Sopitta Thurachen, Josef Taher, Matti Lehtomäki +6
Accurate land cover mapping in riverine environments is essential for effective river management, ecological understanding, and geomorphic change monitoring. This study explores th…
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…
Unsupervised semantic segmentation of urban high-density multispectral point clouds
Oona Oinonen, Lassi Ruoppa, Josef Taher +7
The availability of highly accurate urban airborne laser scanning (ALS) data will increase rapidly in the future, especially as acquisition costs decrease, for example through the…