Mapping European Spruce Bark Beetle Infestation at Its Early Phase Using Gyrocopter-Mounted Hyperspectral Data and Field Measurements

Hellwig, Florian M.; Stelmaszczuk-Górska, Martyna A.; Dubois, Clémence; Wolsza, Marco; Truckenbrodt, Sina; Sagichewski, Herbert; Chmara, Sergej; Bannehr, Lutz; Lausch, Angela; Schmullius, Christiane

doi:10.3390/rs13224659

Cited by 17 publications

(10 citation statements)

References 38 publications

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“…Multispectral sensor systems mounted on aircraft were integrated across all research topics: seven times for forest disturbance, twice for forest cover/type, five times for forest structure, and once each for biodiversity/habitats [45], phenology [3], and plant traits [74]. Hyperspectral data (HySpex and AisaFenix) were evaluated in the areas of forest disturbance [58,68] and plant traits [70,112]. The two publications that made use of airborne radar L-band data (F-SAR and TomoSAR) were assigned to the research topic forest structure [50,86].…”

Section: Review Results: Employed Earth-observation Sensorsmentioning

confidence: 99%

Earth-Observation-Based Monitoring of Forests in Germany—Recent Progress and Research Frontiers: A Review

Holzwarth,

Thonfeld,

Kacic

et al. 2023

Remote Sensing

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One-third of Germany’s land surface area is covered by forest (around 11.4 million hectares), and thus, it characterizes the landscape. The forest is a habitat for a large number of animal and plant species, a source of raw materials, important for climate protection, and a well-being refuge for people, to name just a few of its many functions. During the annual forest condition surveys, the crown condition of German forests is assessed on the basis of field samples at fixed locations, as the crown condition of forest trees is considered an important indicator of their vitality. Since the start of the surveys in 1984, the mean crown defoliation of all tree species has increased, now averaging about 25% for all tree species. Additionally, it shows a strong rise in the rate of dieback. In 2019, the most significant changes were observed. Due to the drastic changes in recent years, efforts are being made to assess the situation of the forest using different remote sensing methods. There are now a number of freely available products provided to the public, and more will follow as a result of numerous projects in the context of earth-observation (EO)-based monitoring and mapping of the forests in Germany. In 2020, the situation regarding the use of remote sensing for the German forest was already investigated in more detail. However, these results no longer reflect the current situation. The changes of the last 3 years are the content of this publication. For this study, 84 citable research publications were thoroughly analyzed and compared with the situation in 2020. As a major result, we found a shift in the research focus towards disturbance monitoring and a tendency to cover larger areas, including national-scale studies. In addition to the review of the scientific literature, we also reviewed current research projects and related products. In congruence to the recent developments in terms of publications in scientific journals, these projects and products reflect the need for comprehensive, timely, large-area, and complementary EO-based information around forests expressed in multiple political programs. With this review, we provide an update of previous work and link it to current research activities. We conclude that there are still gaps between the information needs of forest managers who usually rely on information from field perspectives and the EO-based information products.

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Section: Review Results: Employed Earth-observation Sensorsmentioning

confidence: 99%

Earth-Observation-Based Monitoring of Forests in Germany—Recent Progress and Research Frontiers: A Review

Holzwarth,

Thonfeld,

Kacic

et al. 2023

Remote Sensing

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“…Although the red and gray crowns can be identified distinctly using spectral information acquired from optical imagery, it is too late by then to remove the infested trees for controlling the infestation spread [20]. However, due to the disruption of water transport tissues caused by pest boring, the water content of needles undergoes significant change during the green attack.…”

Section: Introductionmentioning

confidence: 99%

Individual Tree-Level Monitoring of Pest Infestation Combining Airborne Thermal Imagery and Light Detection and Ranging

Wang,

Lin,

Meng

et al. 2024

Forests

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The infestation of pine shoot beetles (Tomicus spp.) in the forests of Southwestern China has inflicted serious ecological damages to the environment, causing significant economic losses. Therefore, accurate and practical approaches to detect pest infestation have become an urgent necessity to mitigate these harmful consequences. In this study, we explored the efficiency of thermal infrared (TIR) technology in capturing changes in canopy surface temperature (CST) and monitoring forest health at the scale of individual tree crowns. We combined data collected from TIR imagery and light detection and ranging (LiDAR) using unmanned airborne vehicles (UAVs) to estimate the shoot damage ratio (SDR), which is a representative parameter of the damage degree caused by forest infestation. We compared multiple machine learning methods for data analysis, including random forest (RF), partial least squares regression (PLSR), and support vector machine (SVM), to determine the optimal regression model for assessing SDR at the crown scale. Our findings showed that a combination of LiDAR metrics and CST presents the highest accuracy in estimating SDR using the RF model (R2 = 0.7914, RMSE = 15.5685). Our method enables the accurate remote monitoring of forest health and is expected to provide a novel approach for controlling pest infestation, minimizing the associated damages caused.

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“…This is useful to quantify damages but not to detect infestations at their early stages (green phase), which would be needed in order to promptly map new infestation spots and take effective actions to contain the outbreak by removing infested trees before offspring emergence (Abdullah et al, 2019;Fernandez-Carrillo et al, 2020;Huo et al, 2021;Bárta et al, 2022). Previous works investigated the effectiveness of combining remote sensing technology with machine learning models to detect early vegetation stress symptoms, using images acquired both by satellites (Meddens et al, 2011;Abdullah et al, 2018;Huo et al, 2020Huo et al, , 2021, airplanes (Hellwig et al, 2021) and drones (Näsi et al, 2015;Otsu et al, 2019;Honkavaara et al, 2020;Yu et al, 2021;Huo et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Drone-based early detection of bark beetle infested spruce trees differs in endemic and epidemic populations

Bozzini,

Brugnaro,

Morgante

et al. 2024

Front. For. Glob. Change

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IntroductionEuropean forests face increasing threats due to climate change-induced stressors, which create the perfect conditions for bark beetle outbreaks. The most important spruce forest pest in Europe is the European Spruce Bark Beetle (Ips typographus L.). Effective management of I. typographus outbreaks necessitates the timely detection of recently attacked spruce trees, which is challenging given the difficulty in spotting symptoms on infested tree crowns. Bark beetle population density is one of many factors that can affect infestation rate and symptoms development. This study compares the appearance of early symptoms in endemic and epidemic bark beetle populations using highresolution Unmanned Aerial Vehicles (UAV) multispectral imagery.MethodsIn spring of 2022, host colonization by bark beetles was induced on groups of spruce trees growing in 10 sites in the Southern Alps, characterized by different population density (5 epidemic and 5 endemic). A multispectral sensor mounted on a drone captured images once every 2 weeks, from May to August 2022. The analyses of a set of vegetational indices allowed the actual infested trees’ reflectance features and symptoms appearance to be observed at each site, comparing them with those of unattacked trees.ResultsResults show that high bark beetles population density triggers a more rapid and intense response regarding the emergence of symptoms. Infested trees were detected at least 1 month before symptoms became evident to the human eye (red phase) in epidemic sites, while this was not possible in endemic sites. Key performing vegetation indices included NDVI (Normalized Difference Vegetation Index), SAVI (Soil Adjust Vegetation Index, with a correction factor of 0.44), and NDRE (Normalized Difference Red Edge index).DiscussionThis early-detection approach could allow automatic diagnosis of bark beetles’ infestations and provide useful guidance for the management of areas suffering pest outbreaks.

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Mapping European Spruce Bark Beetle Infestation at Its Early Phase Using Gyrocopter-Mounted Hyperspectral Data and Field Measurements

Cited by 17 publications

References 38 publications

Earth-Observation-Based Monitoring of Forests in Germany—Recent Progress and Research Frontiers: A Review

Earth-Observation-Based Monitoring of Forests in Germany—Recent Progress and Research Frontiers: A Review

Individual Tree-Level Monitoring of Pest Infestation Combining Airborne Thermal Imagery and Light Detection and Ranging

Drone-based early detection of bark beetle infested spruce trees differs in endemic and epidemic populations

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