Assessing Insecticide Effects in Forests: A Tree-Level Approach Using Unmanned Aerial Vehicles

2019 ◽  
Vol 112 (6) ◽  
pp. 2686-2694
Author(s):  
Benjamin M L Leroy ◽  
Martin M Gossner ◽  
Florian P M Lauer ◽  
Ralf Petercord ◽  
Sebastian Seibold ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Large Scale ◽  
Feeding Activity ◽  
Field Studies ◽  
Tree Level ◽  
Biological Traits ◽  
Thaumetopoea Processionea ◽  
Aerial Vehicles ◽  
Large Scale Field ◽  
Individual Trees

Abstract Large-scale field studies on the ecological effects of aerial forest spraying often face methodological challenges, such as insufficient funding, difficult logistics, and legal obstacles. The resulting routine use of underpowered designs could lead to a systematic underestimation of insecticide effects on nontarget arthropod communities. We tested the use of an Unmanned Aerial Vehicles (UAVs) for experimental insecticide applications at tree level to increase replication in cost-efficient way. We assessed the effects of two forestry insecticides, diflubenzuron (DFB) and tebufenozide (TBF), on the oak defoliator, Thaumetopoea processionea (Linnaeus) (Lepidoptera: Thaumetopoeidae), and on nontarget, tree-living Lepidoptera. Individual trees were sprayed with either insecticide or left unsprayed, in a fully factorial design involving 60 trees. Caterpillars fallen from tree crowns were sampled as a measure of mortality, while caterpillar feeding activity was monitored by collecting frass droppings. Both DFB and TBF led to greater mortality of T. processionea and lower Lepidoptera feeding activity than control levels. TBF caused measurable mortality in nontarget groups, affecting Macrolepidoptera more strongly than Microlepidoptera, while there was no significant side effect of DFB. The high treatment efficacy against the target pest indicates that UAV technology is well-suited for the application of insecticide in forests. We detected distinct responses to different insecticides among nontarget groups and suggest there is an influence of application timing and biological traits in these differences, emphasizing the need for more ecologically orientated risk assessment. UAV-supported designs can be used to link laboratory bioassays and large-scale experiments, allowing for more comprehensive assessments of insecticide effects in forest ecosystems.

scholarly journals Occupational exoskeletons: A roadmap toward large-scale adoption. Methodology and challenges of bringing exoskeletons to workplaces

2021 ◽  
Vol 2 ◽  
Author(s):  
Simona Crea ◽  
Philipp Beckerle ◽  
Michiel De Looze ◽  
Kevin De Pauw ◽  
Lorenzo Grazi ◽  
...  
Keyword(s):  
Large Scale ◽  
Health And Safety ◽  
Field Studies ◽  
Specific Work ◽  
Safety Standards ◽  
Knowledge Based ◽  
Scientific Papers ◽  
Large Scale Field ◽  
Standards And Regulations ◽  
Definition Of

Abstract The large-scale adoption of occupational exoskeletons (OEs) will only happen if clear evidence of effectiveness of the devices is available. Performing product-specific field validation studies would allow the stakeholders and decision-makers (e.g., employers, ergonomists, health, and safety departments) to assess OEs’ effectiveness in their specific work contexts and with experienced workers, who could further provide useful insights on practical issues related to exoskeleton daily use. This paper reviews present-day scientific methods for assessing the effectiveness of OEs in laboratory and field studies, and presents the vision of the authors on a roadmap that could lead to large-scale adoption of this technology. The analysis of the state-of-the-art shows methodological differences between laboratory and field studies. While the former are more extensively reported in scientific papers, they exhibit limited generalizability of the findings to real-world scenarios. On the contrary, field studies are limited in sample sizes and frequently focused only on subjective metrics. We propose a roadmap to promote large-scale knowledge-based adoption of OEs. It details that the analysis of the costs and benefits of this technology should be communicated to all stakeholders to facilitate informed decision making, so that each stakeholder can develop their specific role regarding this innovation. Large-scale field studies can help identify and monitor the possible side-effects related to exoskeleton use in real work situations, as well as provide a comprehensive scientific knowledge base to support the revision of ergonomics risk-assessment methods, safety standards and regulations, and the definition of guidelines and practices for the selection and use of OEs.

scholarly journals Detecting Individual Tree Attributes and Multispectral Indices Using Unmanned Aerial Vehicles: Applications in a Pine Clonal Orchard

2020 ◽  
Vol 12 (24) ◽  
pp. 4144
Author(s):  
José Luis Gallardo-Salazar ◽  
Marín Pompa-García
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Field Measurements ◽  
Tree Level ◽  
Individual Tree ◽  
Basal Diameter ◽  
Crown Diameter ◽  
Aerial Vehicles

Modern forestry poses new challenges that space technologies can solve thanks to the advent of unmanned aerial vehicles (UAVs). This study proposes a methodology to extract tree-level characteristics using UAVs in a spatially distributed area of pine trees on a regular basis. Analysis included different vegetation indices estimated with a high-resolution orthomosaic. Statistically reliable results were found through a three-phase workflow consisting of image acquisition, canopy analysis, and validation with field measurements. Of the 117 trees in the field, 112 (95%) were detected by the algorithm, while height, area, and crown diameter were underestimated by 1.78 m, 7.58 m2, and 1.21 m, respectively. Individual tree attributes obtained from the UAV, such as total height (H) and the crown diameter (CD), made it possible to generate good allometric equations to infer the basal diameter (BD) and diameter at breast height (DBH), with R2 of 0.76 and 0.79, respectively. Multispectral indices were useful as tree vigor parameters, although the normalized-difference vegetation index (NDVI) was highlighted as the best proxy to monitor the phytosanitary condition of the orchard. Spatial variation in individual tree productivity suggests the differential management of ramets. The consistency of the results allows for its application in the field, including the complementation of spectral information that can be generated; the increase in accuracy and efficiency poses a path to modern inventories. However, the limitation for its application in forests of more complex structures is identified; therefore, further research is recommended.

Optimal flight parameters for unmanned aerial vehicles collecting spatial information for estimating large-scale waste generation

2019 ◽  
Vol 40 (20) ◽  
pp. 8010-8030 ◽  
Author(s):  
Seung Woo Son ◽  
Jeong Ho Yoon ◽  
Hyung Jin Jeon ◽  
Dong Woo Kim ◽  
Jae Jin Yu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Large Scale ◽  
Spatial Information ◽  
Waste Generation ◽  
Aerial Vehicles ◽  
Flight Parameters

scholarly journals Methodological Ambiguity and Inconsistency Constrain Unmanned Aerial Vehicles as A Silver Bullet for Monitoring Ecological Restoration

2019 ◽  
Vol 11 (10) ◽  
pp. 1180 ◽  
Author(s):  
Todd M. Buters ◽  
Philip W. Bateman ◽  
Todd Robinson ◽  
David Belton ◽  
Kingsley W. Dixon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Unmanned Aerial Vehicles ◽  
Ecological Restoration ◽  
Large Scale ◽  
Ecological Monitoring ◽  
Policy Framework ◽  
Strong Positive Correlation ◽  
Aerial Vehicles ◽  
The Future ◽  
Thermal Cameras

The last decade has seen an exponential increase in the application of unmanned aerial vehicles (UAVs) to ecological monitoring research, though with little standardisation or comparability in methodological approaches and research aims. We reviewed the international peer-reviewed literature in order to explore the potential limitations on the feasibility of UAV-use in the monitoring of ecological restoration, and examined how they might be mitigated to maximise the quality, reliability and comparability of UAV-generated data. We found little evidence of translational research applying UAV-based approaches to ecological restoration, with less than 7% of 2133 published UAV monitoring studies centred around ecological restoration. Of the 48 studies, > 65% had been published in the three years preceding this study. Where studies utilised UAVs for rehabilitation or restoration applications, there was a strong propensity for single-sensor monitoring using commercially available RPAs fitted with the modest-resolution RGB sensors available. There was a strong positive correlation between the use of complex and expensive sensors (e.g., LiDAR, thermal cameras, hyperspectral sensors) and the complexity of chosen image classification techniques (e.g., machine learning), suggesting that cost remains a primary constraint to the wide application of multiple or complex sensors in UAV-based research. We propose that if UAV-acquired data are to represent the future of ecological monitoring, research requires a) consistency in the proven application of different platforms and sensors to the monitoring of target landforms, organisms and ecosystems, underpinned by clearly articulated monitoring goals and outcomes; b) optimization of data analysis techniques and the manner in which data are reported, undertaken in cross-disciplinary partnership with fields such as bioinformatics and machine learning; and c) the development of sound, reasonable and multi-laterally homogenous regulatory and policy framework supporting the application of UAVs to the large-scale and potentially trans-disciplinary ecological applications of the future.

Minimizing the number of wireless charging PAD for unmanned aerial vehicle–based wireless rechargeable sensor networks

2021 ◽  
Vol 17 (12) ◽  
pp. 155014772110559
Author(s):  
Yingjue Chen ◽  
Yingnan Gu ◽  
Panfeng Li ◽  
Feng Lin
Keyword(s):  
Sensor Networks ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Large Scale ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Charging ◽  
Aerial Vehicles ◽  
Wireless Rechargeable Sensor Networks ◽  
Aerial Vehicle

In wireless rechargeable sensor networks, most researchers address energy scarcity by introducing one or multiple ground mobile vehicles to recharge energy-hungry sensor nodes. The charging efficiency is limited by the moving speed of ground chargers and rough environments, especially in large-scale or challenging scenarios. To address the limitations, researchers consider replacing ground mobile chargers with lightweight unmanned aerial vehicles to support large-scale scenarios because of the unmanned aerial vehicle moving at a higher speed without geographical limitation. Moreover, multiple automatic landing wireless charging PADs are deployed to recharge unmanned aerial vehicles automatically. In this work, we investigate the problem of introducing the minimal number of PADs in unmanned aerial vehicle–based wireless rechargeable sensor networks. We propose a novel PAD deployment scheme named clustering-with-double-constraints and disks-shift-combining that can adapt to arbitrary locations of the base station, arbitrary geographic distributions of sensor nodes, and arbitrary sizes of network areas. In the proposed scheme, we first obtain an initial PAD deployment solution by clustering nodes in geographic locations. Then, we propose a center shift combining algorithm to optimize this solution by shifting the location of PADs and attempting to merge the adjacent PADs. The simulation results show that compared to existing algorithms, our scheme can charge the network with fewer PADs.

Effects of oviposition by periodical cicadas on tree growth

2009 ◽  
Vol 39 (9) ◽  
pp. 1688-1697 ◽  
Author(s):  
Keith Clay ◽  
Angela L. Shelton ◽  
Chuck Winkle
Keyword(s):  
Tree Growth ◽  
Tree Species ◽  
Large Scale ◽  
Field Studies ◽  
Detectable Effect ◽  
Periodical Cicadas ◽  
Annual Growth Rings ◽  
Large Scale Field ◽  
Successional Forests ◽  
Long Term Impact

Periodical cicadas ( Magicicada spp.) occur at very high densities and synchronously emerge from underground every 13 or 17 years. During the emergence, adults lay eggs in tree branches, causing significant damage; however, the long-term impact of this damage is unknown. We conducted two large-scale field studies during the 2004 emergence of one brood (Brood X) to measure the growth of trees in relation to oviposition damage by periodical cicadas. In the first experiment, we netted areas to exclude cicadas from plots in 15 early successional forests and then measured trunk circumference for 3 years on more than 4000 trees of 52 species. In this experiment, oviposition had no detectable effect on the growth rates of trees. In the second study, we measured oviposition on 12 common tree species across six sites. We then measured the annual growth rings of these trees for 3 years after the emergence. In this experiment, oviposition was correlated with a slightly reduced growth in the emergence year and following year when the data were analyzed together, but when tree species were examined individually there were no clear effects of oviposition on tree growth. These data suggest cicada oviposition has little effect on the radial growth of trees, particularly in comparison to other factors.

scholarly journals Robust Detection, Classification and Localization of Defects in Large Photovoltaic Plants Based on Unmanned Aerial Vehicles and Infrared Thermography

2020 ◽  
Vol 10 (17) ◽  
pp. 5948 ◽  
Author(s):  
Alberto Fernández ◽  
Rubén Usamentiaga ◽  
Pedro de Arquer ◽  
Miguel Ángel Fernández ◽  
D. Fernández ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Infrared Thermography ◽  
Large Scale ◽  
Cost Effective ◽  
Electrical Performance ◽  
Performance Measurements ◽  
Robust Detection ◽  
Aerial Vehicles ◽  
Pv Modules

The efficiency and profitability of photovoltaic (PV) plants are highly controlled by their operation and maintenance (O&M) procedures. Today, the effective diagnosis of any possible fault of PV plants remains a technical and economic challenge, especially when dealing with large-scale PV plants. Currently, PV plant monitoring is carried out by either electrical performance measurements or image processing. The first approach presents limited fault detection ability, it is costly and time-consuming, and it is incapable of fast identification of the physical location of the fault. In the second approach, Infrared Thermography (IRT) imaging has been used for the characterization of PV module failures, but their setup and processing are rather complex and an experienced technician is required. The use of Unmanned Aerial Vehicles (UAVs) for IRT imaging of PV plants for health status monitoring of PV modules has been identified as a cost-effective approach that offers 10–-15 fold lower inspection times than conventional techniques. However, previous works have not performed a comprehensive approach in the context of automated UAV inspection using IRT. This work provides a fully automated approach for the: (a) detection, (b) classification, and (c) geopositioning of the thermal defects in the PV modules. The system has been tested on a real PV plant in Spain. The obtained results indicate that an autonomous solution can be implemented for a full characterization of the thermal defects.

scholarly journals Distributed Leader-Follower Flight Control for Large-Scale Clusters of Small Unmanned Aerial Vehicles

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 32790-32799 ◽  
Author(s):  
Yongnan Jia ◽  
Qing Li ◽  
Shanqiao Qiu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Flight Control ◽  
Large Scale ◽  
Aerial Vehicles
Sign in / Sign up

Export Citation Format

Share Document