5 papers
A Framework for Individual Tree Growth Reconstruction Using Multi-Platform Laser Scanning
Daniella Tavi, Valtteri Soininen, Lassi Ruoppa +2
Accurate tree-level forest monitoring using laser scanning data requires reliable tree delineation, consistent tree correspondence across multitemporal point clouds, and accurate e…
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…
3D forest semantic segmentation using multispectral LiDAR and 3D deep learning
Narges Takhtkeshha, Lauris Bocaux, Lassi Ruoppa +4
Conservation and decision-making regarding forest resources necessitate regular forest inventory. Light detection and ranging (LiDAR) in laser scanning systems has gained significa…
Unsupervised deep learning for semantic segmentation of multispectral LiDAR forest point clouds
Lassi Ruoppa, Oona Oinonen, Josef Taher +5
Point clouds captured with laser scanning systems from forest environments can be utilized in a wide variety of applications within forestry and plant ecology, such as the estimati…
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…