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Cost comparison of drone and foot based early bark beetle detection
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1  Georg-August-University Göttingen, Faculty of Forest Science and Forest Ecology, Dept. of Forest Work Science and Engineering
Academic Editor: Lotus Guo

Abstract:

Early bark beetle detection is still a challenge, as the symptoms of early infestation stages are hard to identify. Conventional foot-based detection is time consuming and the associated costs depend on the stand characteristics. A detection by gas sensor equipped drones can decrease the costs, as it does not rely on the movement speed on the ground. A novel drone-based system for early bark beetle detection by means of resin odor cues was compared to a conventional foot-based detection. The results showed that the cost efficiency of the drone system highly depends on the flight speed and the hourly costs of the pilot, while the cost efficiency of the foot-based assessment highly depends on the terrain slope and the forest floor characteristics. In general, the drone-based detection of early infestation stages showed increasing cost reductions in comparison to the conventional detection at increasing forest areas, increasing slopes and increasing understory density.

Keywords: UAV, conifer forest, walking speed, electronic nose
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