3D Hyperspectral and Thermal Analysis of Forest Trees Focusing on Bark Beetle Infestation
Résumé
Disturbances caused by bark beetles are a massive problem for forestry in the northern hemisphere. Especially the central part of the national parks Bavarian Forest (Germany) and umava (Czech Republic) are often affected by bark beetle infestations. Recently, an early stage detection of bark beetle infestation is only possible by terrestrial inspection, which is labor intensive and costly. Thus, effective methods allowing an early-stage detection of bark beetle infestation of larger areas are needed. The joint project BarkBeeDet aims at investigating the detection of trees infested by bark beetle at an early stage (green-attack-stage) using methods of UAV (Unmanned Air Vehicle)-based imaging with LiDAR, hyperspectral and thermal IR sensors. The data of the different sensors is used in conjunction for image analysis, whereas methods of 3D object-based image analysis are applied. The paper present outlines first results of imaging and 3D object-based image analysis and concludes the potential of this method for an effective detection of bark beetle infestation.