Field demonstration of a wing-beat modulation lidar for the 3D mapping of flying insects

Tauc, Martin Jan; Fristrup, Kurt M.; Repasky, Kevin S.; Shaw, Joseph A.

doi:10.1364/osac.2.000332

Cited by 19 publications

(24 citation statements)

References 38 publications

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“…The data that support the findings of this study are openly available in [OSA Publishing] at https://doi.org/%5B10.1364/OPEX.13.005853], (Shaw et al, ). The data that support the findings of this study are openly available in [OSA Publishing] at https://doi.org/%5B10.1364/OSAC.2.000332], (Tauc et al, ). The data that support the findings of this study are openly available in [OSA Publishing] at https://doi.org/%5B10.1364/AO.57.010164], (Zhai, ).…”

Section: Data Availability Statementsupporting

confidence: 75%

“…Since our detection system has a high read‐out frequency, it is possible to capture the wing movements and thus the wing‐beat frequency of insects (Brydegaard, ; Brydegaard et al, ; Repasky et al, ; Tauc, Fristrup, Repasky, & Shaw, ; Zhu et al, ). This property by itself is insufficient for fully characterizing insects, but still provides valuable information regarding the flying fauna.…”

Section: Methodsmentioning

confidence: 99%

“…The absence of beats in raindrop signals can also be used for discrimination, but was not employed here since it is computationally more intensive. Since our detection system has a high read-out frequency, it is possible to capture the wing movements and thus the wing-beat frequency of insects (Brydegaard, 2015;Brydegaard et al, 2014;Repasky et al, 2006;Tauc, Fristrup, Repasky, & Shaw, 2019;Zhu et al, 2017).…”

Section: Materials S and Me Thodsmentioning

confidence: 99%

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Application of lidar remote sensing of insects in agricultural entomology on the Chinese scene

Song

Zhang

Feng

et al. 2019

J Applied Entomology

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Insect pest management is a very important aspect for plant protection in crops production. Remote sensing provides a large number of techniques that are beneficial in entomological research. Although entomological radars have been used for studying migrations of insects for many years, most of entomological radar studies have been vertically tracing high‐altitude migration behaviour of insects. Light detection and ranging (lidar) is a counterpart to radar, now operating in the optical part of the electromagnetic spectrum, which has been recently applied for monitoring of insects at low altitude. Such techniques, in particular low‐cost continuous‐wave (CW) bi‐static systems based on the Scheimpflug arrangement, have been rapidly developing during the last decade. As a result, optical methods present new and fascinating possibilities. Based on experience from a 2‐week field campaign in rice paddy fields, we here present an overview of lidar remote sensing applied to the Chinese scene. The capability of a CW Scheimpflug lidar system in monitoring the insects was studied. We present results on insect abundance in relation to time of the day and weather conditions. We also identified insect species by analysing wing‐beat frequencies and studied their attraction to ultraviolet (UV) lamp located close to the horizontal laser sampling path during night time. Results showed that the insect species were abundant, that insects detected by the lidar system were attracted to light and that light rain increased the insect activity. The lidar detection system had a high read‐out frequency, enabling the estimation of insect wing‐beat frequencies.

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Section: Data Availability Statementsupporting

confidence: 75%

Section: Methodsmentioning

confidence: 99%

Section: Materials S and Me Thodsmentioning

confidence: 99%

See 1 more Smart Citation

Application of lidar remote sensing of insects in agricultural entomology on the Chinese scene

Song

Zhang

Feng

et al. 2019

J Applied Entomology

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“…Such identifications are possible due to predictor variables retrieved from interactions of the insect with light. For instance, the wing beat frequency and harmonics content of flying insects retrieved from entomological lidar signals have been used to differentiate between species . The wing beat frequency has also been used to discriminate sex and identify mosquito species in particular .…”

Section: Introductionmentioning

confidence: 99%

“…They can monitor thousands of insects in the span of a few hours without the need for expensive and laborious taxonomic analysis in a laboratory. Furthermore, such systems can record the flight trajectory or position of the insects in real time , enabling the identification of high‐risk areas for targeted mitigation techniques, and the study of predator‐prey dynamics or mating behavior if coupled with species and sex identification. Such identifications are possible due to predictor variables retrieved from interactions of the insect with light.…”

Section: Introductionmentioning

confidence: 99%

Identification of gravid mosquitoes from changes in spectral and polarimetric backscatter cross sections

Genoud

Gao

Williams

et al. 2019

Journal of Biophotonics

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Improving the survey of mosquito populations is of the utmost importance to further enhance mitigation techniques that protect human populations from mosquito‐borne diseases. While mosquito populations are generally studied using physical traps, stand‐off optical sensors allow to study insect ecosystems with potentially better spatial and temporal resolution. This can be greatly beneficial to eco‐epidemiological models and various mosquito control programs. In this contribution, we demonstrate that the gravidity of female mosquitoes can be identified from changes in their spectral and polarimetric backscatter cross sections. Among other predictive variables, the wing beat frequency and the depolarization ratio of the mosquito body allows for the identification of gravid females with a precision and recall of 86% and 87%, respectively. Since female mosquitoes need a blood meal to become gravid, statistics on gravidity is of prime importance as only females that have been gravid might carry infectious diseases. In addition, it allows to detect possible breeding habitat, predict a potential increase in the mosquito population and provide a better overall understanding of the ecosystem dynamics. As a result, targeted and localized mitigation techniques can be used, reducing the cost and improving the efficiency of mosquito population control.

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A comparison of supervised machine learning algorithms for mosquito identification from backscattered optical signals

Genoud

Gao

Williams

et al. 2020

Ecological Informatics

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Field demonstration of a wing-beat modulation lidar for the 3D mapping of flying insects

Cited by 19 publications

References 38 publications

Application of lidar remote sensing of insects in agricultural entomology on the Chinese scene

Application of lidar remote sensing of insects in agricultural entomology on the Chinese scene

Identification of gravid mosquitoes from changes in spectral and polarimetric backscatter cross sections

A comparison of supervised machine learning algorithms for mosquito identification from backscattered optical signals

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