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Project PROTECTFOREST©: Early detection of bark beetle infestation by drone-based monoterpene detection
* 1 , 2 , 3 , 1
1  Georg-August-University Göttingen, Faculty of Forest Science and Forest Ecology, Dept. of Forest Work Science and Engineering
2  University of Freiburg Germany, Chair of Remote Sensing and Landscape Information Systems
3  Technical University Rottenburg

Abstract:

Early detection of bark beetle infestation is a costly and time consuming task, as it can only be done reliable by personal screening the crowns for resin flow. Drone based detection systems prooved to be able to detect bark beetle infestation in the "red crown" stage. This is insufficient for a fast response under increasing infestation rates, as either the work load is very high or the tree is detected after the beetles have already multiplied and infested other trees. Therefore, a fast response method is needed to detect infested trees in the "green" stage. In this stage, only the hardly visible optical impression of the resin flow and the resin odor are detection cues.

A semi-conductor gas sensor containing three gas sensor elements was designed and integrated on a drone platform to detect monoterpene emissions over the crowns of a mixed deciduous/conifer forest. The sensor system was calibrated in the lab and tested under artificial lab and field conditions. The detection of alpha Pinen, the predominant mono terpene emitted by conifer resin, prooved to be successful. The detection of infested trees was prooven to be technical and chemo-ecologically possible. Heat Maps of stands with infested trees were generated in field trials and interpreted under additional information of the wind movement detected by a second drone.

This early detection concept can improve the fast response of foresters in order to protect conifer stands from bark beetle gradation. Further work is dedicated to the complete automation of the sensor drone flight and the Heat Map generation in order to transfer the measuring concept into the operational flow of forest management.

Keywords: VOC detection; drone sensor; spruce infestation; gas sensor
Comments on this paper
Rodolfo Picchio
Session Chair comment
Dear Authors,

Congratulations for this study. The project You have been carrying out is as much challenging as the issue of bark beetle infestation is crucial in many local and broad areas. The integrated approach based on gas sensor system and drone technology introduces an encouraging perspective to gain a fast and cost-affordable detection of bark beetle gradation, in order to provide forest management of a helpful assessment protocol. I hope to read about this research in some full papers soon.

Session Chair

Rodolfo Picchio

Rodolfo Picchio
Session Chair comment
Dear Authors,

Congratulations for this study. The project You have been carrying out is as much challenging as the issue of bark beetle infestation is crucial in many local and broad areas. The integrated approach based on gas sensor system and drone technology introduces an encouraging perspective to gain a fast and cost-affordable detection of bark beetle gradation, in order to provide forest management of a helpful assessment protocol. I hope to read about this research in some full papers soon.

Session Chair

Rodolfo Picchio



 
 
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