5 papers
3D LULC classification using multispectral LiDAR and deep learning: current and prospective schemes
Narges Takhtkeshha, Aldino Rizaldy, Markus Hollaus +3
Land Use Land Cover (LULC) classification is essential for national 3D mapping, geospatial analysis, and sustainable planning. Multispectral (MS) LiDAR provides synchronized spatia…
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…
Multispectral LiDAR data for extracting tree points in urban and suburban areas
Narges Takhtkeshha, Gabriele Mazzacca, Fabio Remondino +2
Monitoring urban tree dynamics is vital for supporting greening policies and reducing risks to electrical infrastructure. Airborne laser scanning has advanced large-scale tree mana…
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…