7 papers
Field evaluation and optimization of a lightweight autonomous lidar-based UAV system based on a rigorous experimental setup in boreal forest environments
Aleksi Karhunen, Teemu Hakala, Väinö Karjalainen +1
Interest in utilizing autonomous uncrewed aerial vehicles (UAVs) for under-canopy forest remote sensing has increased in recent years, resulting in the publication of numerous auto…
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…
Towards autonomous photogrammetric forest inventory using a lightweight under-canopy robotic drone
Väinö Karjalainen, Niko Koivumäki, Teemu Hakala +5
Drones are increasingly used in forestry to capture high-resolution remote sensing data, supporting enhanced monitoring, assessment, and decision-making processes. While operations…
Deep Learning-based Robust Autonomous Navigation of Aerial Robots in Dense Forests
Guglielmo Del Col, Väinö Karjalainen, Teemu Hakala +2
Autonomous aerial navigation in dense natural environments remains challenging due to limited visibility, thin and irregular obstacles, GNSS-denied operation, and frequent perceptu…
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…
Detecting Wildfires on UAVs with Real-time Segmentation Trained by Larger Teacher Models
Julius Pesonen, Teemu Hakala, Väinö Karjalainen +6
Early detection of wildfires is essential to prevent large-scale fires resulting in extensive environmental, structural, and societal damage. Uncrewed aerial vehicles (UAVs) can co…