Autonomous unmanned aerial vehicles (UAV), flying robots, are utilized increasingly in our society. They can capture data of the environment rapidly and safely. Sensors and analytics make UAVs intelligent. Finnish Geospatial Research Institute and University of Jyväskylä jointly formed the ASPECT-research consortium, which developed an autonomous UAV-based tree health analyzer based on imaging spectroscopy and machine learning. ASPECT-consortium was a multidisciplinary team covering geoinformatics, remote sensing, photogrammetry, hyperspectral imaging, computer, computational, and automation sciences.The project responses to the urgent need of developing efficient technologies for canopy health monitoring that are needed due to increasing frequency and severity of forest disturbance due to climate change.
