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3D Hyperspectral and Thermal Analysis of Forest Trees Focusing on Bark Beetle Infestation

Abstract : 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.
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Submitted on : Tuesday, December 18, 2018 - 8:29:27 AM
Last modification on : Friday, December 3, 2021 - 11:26:02 AM


  • HAL Id : hal-01958426, version 1



Peter Hofmann, Martin Hais, Marco Heurich, Rainer Pöschl, Stefan Kunze, et al.. 3D Hyperspectral and Thermal Analysis of Forest Trees Focusing on Bark Beetle Infestation. GEOBIA 2018 - From pixels to ecosystems and global sustainability ​, Centre d'Etudes Spatiales de la BIOsphère (CESBIO); Office national d'études et de recherches aérospatiales (ONERA); Espace pour le développement (ESPACE DEV); UMR TETIS, Jun 2018, Montpellier, France. ⟨hal-01958426⟩



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