Evaluation of Early Bark Beetle Infestation Localization by Drone-Based Monoterpene Detection

Paczkowski, Sebastian; Datta, Pawan; Irion, Heidrun; Paczkowska, Marta; Habert, Thilo; Pelz, Stefan; Jaeger, Dirk

doi:10.3390/f12020228

Cited by 10 publications

(11 citation statements)

References 51 publications

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“…Measuring chemical substances using electronic noses is a promising methodology in forestry [ 12 , 21 ]. This system is already verified for monitoring odors from agricultural farms and dangerous gas leaks from industrial sites [ 41 , 42 , 43 , 44 ].…”

Section: Discussionmentioning

confidence: 99%

“…In agriculture, these sensors have been used to detect odors from livestock, hazardous chemical, biological compounds, and for early detection and prediction of pest insects (for example: Aphid Infestation, Lepidoptera) [ 19 , 20 ]. In forestry, it is possible with these sensors to detect VOCs and other chemical components, which can identify stress factors [ 12 , 21 ]. Other sensors include H 2 S, HCL, nitrogen, and next SO 2 , CO, O 3 , NO 2 , and, for example, sensors for measuring the content of dust particles in the air (PM 1.0 , PM 2.5 , PM 10 ).…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Individual Sensors in the Electronic Nose for Stress Detection in Forest Stands

Hüttnerová

Paczkowski

Neubert

et al. 2023

Sensors

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Forests are increasingly exposed to natural disturbances, including drought, wildfires, pest outbreaks, and windthrow events. Due to prolonged droughts in the last years in Europe, European forest stands significantly lost vitality, and their health condition deteriorated, leading to high mortality rates, especially, but not limited to, Norway spruce. This phenomenon is growing, and new regions are being affected; thus, it is necessary to identify stress in the early stages when actions can be taken to protect the forest and living trees. Current detection methods are based on field walks by forest workers or deploying remote sensing methods for coverage of the larger territory. These methods are based on changes in spectral reflectance that can detect attacks only at an advanced stage after the significant changes in the canopy. An innovative approach appears to be a method based on odor mapping, specifically detecting chemical substances which are present in the forest stands and indicate triggering of constitutive defense of stressed trees. The bark beetle attacking a tree, for example, produces a several times higher amount of defense-related volatile organic compounds. At the same time, the bark beetle has an aggregation pheromone to attract conspecifics to overcome the tree defense by mass attack. These substances can be detected using conventional chemical methods (solid-phase microextraction fibers and cartridges), and it is proven that they are detectable by dogs. The disadvantage of classic chemical analysis methods is the long sampling time in the forest, and at the same time, the results must be analyzed in the laboratory using a gas chromatograph. A potential alternative novel device appears to be an electronic nose, which is designed to detect chemical substances online (for example, dangerous gas leaks or measure concentrations above landfills, volcanic activity, etc.). We tested the possibility of early-stage stress detection in the forest stands using an electronic nose Sniffer4D and compared the individual sensors in it for detecting the presence of attacked and dead trees. Our results indicate the promising applicability of the electronic nose for stress mapping in the forest ecosystem, and more data collection could prove this approach.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparison of Individual Sensors in the Electronic Nose for Stress Detection in Forest Stands

Hüttnerová

Paczkowski

Neubert

et al. 2023

Sensors

Self Cite

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“…They manually sampled bark-beetle-damaged trees in UAV-based orthomosaics to determine threshold rules for training classifiers based on cellular automata. A single study was devoted to the localization of bark beetle occurrences using a semiconductor gas sensor attached to a UAV to detect monoterpenes that could indicate an early stage of infestation [93]. Alpha pinene could be detected as an artificial source in the field.…”

Section: Biotic Stressors (A) Pestsmentioning

confidence: 99%

“…Nevertheless, RGB and multispectral cameras have dominated the use cases since 2017. The least represented sensors were thermal and gas sensors, with the latter only recently being used in a single study [93]. In about one-third of the studies, multiple sensors usage was described, and most often, the sensors were attached simultaneously to the same UAV.…”

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confidence: 99%

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UAV-Based Forest Health Monitoring: A Systematic Review

et al. 2022

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In recent years, technological advances have led to the increasing use of unmanned aerial vehicles (UAVs) for forestry applications. One emerging field for drone application is forest health monitoring (FHM). Common approaches for FHM involve small-scale resource-extensive fieldwork combined with traditional remote sensing platforms. However, the highly dynamic nature of forests requires timely and repetitive data acquisition, often at very high spatial resolution, where conventional remote sensing techniques reach the limits of feasibility. UAVs have shown that they can meet the demands of flexible operation and high spatial resolution. This is also reflected in a rapidly growing number of publications using drones to study forest health. Only a few reviews exist which do not cover the whole research history of UAV-based FHM. Since a comprehensive review is becoming critical to identify research gaps, trends, and drawbacks, we offer a systematic analysis of 99 papers covering the last ten years of research related to UAV-based monitoring of forests threatened by biotic and abiotic stressors. Advances in drone technology are being rapidly adopted and put into practice, further improving the economical use of UAVs. Despite the many advantages of UAVs, such as their flexibility, relatively low costs, and the possibility to fly below cloud cover, we also identified some shortcomings: (1) multitemporal and long-term monitoring of forests is clearly underrepresented; (2) the rare use of hyperspectral and LiDAR sensors must drastically increase; (3) complementary data from other RS sources are not sufficiently being exploited; (4) a lack of standardized workflows poses a problem to ensure data uniformity; (5) complex machine learning algorithms and workflows obscure interpretability and hinders widespread adoption; (6) the data pipeline from acquisition to final analysis often relies on commercial software at the expense of open-source tools.

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