Towards Quantitative Optical Cross Sections in Entomological Laser Radar - Potential of Temporal and Spherical Parameterizations for Identifying Atmospheric Fauna

The Use and Prospects of Nonlethal Methods in Entomology

Arthropods are declining globally, and entomologists ought to be in the forefront of protecting them. However, entomological study methods are typically lethal, and we argue that this makes the ethical status of the profession precarious. Lethal methods are used in most studies, even those that aim to support arthropod conservation. Additionally, almost all collecting methods result in bycatch, and a first step toward less destructive research practices is to minimize bycatch and/or ensure its proper storage and use. In this review, we describe the available suite of nonlethal methods with the aim of promoting their use. We classify nonlethal methods into (a) reuse of already collected material, (b) methods that are damaging but not lethal, (c) methods that modify behavior, and (d) true nonlethal methods. Artificial intelligence and miniaturization will help to extend the nonlethal methodological toolkit, but the need for further method development and testing remains.

Dual-Band Infrared Scheimpflug Lidar Reveals Insect Activity in a Tropical Cloud Forest

We describe an entomological dual-band 808 and 980 nm lidar system which has been implemented in a tropical cloud forest (Ecuador). The system was successfully tested at a sample rate of 5 kHz in a cloud forest during challenging foggy conditions (extinction coefficients up to 20 km^-1). At times, the backscattered signal could be retrieved from a distance of 2.929 km. We present insect and bat observations up to 200 m during a single night with an emphasis on fog aspects, potentials, and benefits of such dual-band systems. We demonstrate that the modulation contrast between insects and fog is high in the frequency domain compared to intensity in the time domain, thus allowing for better identification and quantification in misty forests. Oscillatory lidar extinction effects are shown in this work for the first time, caused by the combination of dense fog and large moths partially obstructing the beam. We demonstrate here an interesting case of a moth where left- and right-wing movements induced oscillations in both intensity and pixel spread. In addition, we were able to identify the dorsal and ventral sides of the wings by estimating the corresponding melanization with the dual-band lidar. We demonstrate that the wing beat trajectories in the dual-band parameter space are complementary rather than covarying or redundant, thus a dual-band entomological lidar approach to biodiversity studies is feasible in situ and endows species specificity differentiation. Future improvements are discussed. The introduction of these methodologies opens the door to a wealth of possible experiments to monitor, understand, and safeguard the biological resources of one of the most biodiverse countries on Earth.

Automated detection of the yellow-legged hornet (Vespa velutina) using an optical sensor with machine learning

BACKGROUND

The yellow-legged hornet (Vespa velutina) is native to Southeast Asia and is an invasive alien species of concern in many countries. More effective management of populations of V. velutina could be achieved through more widespread and intensive monitoring in the field, however current methods are labor intensive and costly. To address this issue, we have assessed the performance of an optical sensor combined with a machine learning model to classify V. velutina and native wasps/hornets and bees. Our aim is to use the results of the present work as a step towards the development of a monitoring solution for V. velutina in the field.

RESULTS

We recorded a total 935 flights from three bee species: Apis mellifera, Bombus terrestris and Osmia bicornis; and four wasp/hornet species: Polistes dominula, Vespula germanica, Vespa crabro and V. velutina. The machine learning model achieved an average accuracy for species classification of 80.1 ± 13.9% and 74.5 ± 7.0% for V. velutina. V. crabro had the highest level of misclassification, confused mainly with V. velutina and P. dominula. These results were obtained using a 14-value peak and valley feature derived from the wingbeat power spectral density.

CONCLUSION

This study demonstrates that the wingbeat recordings from a flying insect sensor can be used with machine learning methods to differentiate V. velutina from six other Hymenoptera species in the laboratory and this knowledge could be used to help develop a tool for use in integrated invasive alien species management programs. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

A novel optical sensor system for the automatic classification of mosquitoes by genus and sex with high levels of accuracy

Background

Every year, more than 700,000 people die from vector-borne diseases, mainly transmitted by mosquitoes. Vector surveillance plays a major role in the control of these diseases and requires accurate and rapid taxonomical identification. New approaches to mosquito surveillance include the use of acoustic and optical sensors in combination with machine learning techniques to provide an automatic classification of mosquitoes based on their flight characteristics, including wingbeat frequency. The development and application of these methods could enable the remote monitoring of mosquito populations in the field, which could lead to significant improvements in vector surveillance.

Methods

A novel optical sensor prototype coupled to a commercial mosquito trap was tested in laboratory conditions for the automatic classification of mosquitoes by genus and sex. Recordings of > 4300 laboratory-reared mosquitoes of Aedes and Culex genera were made using the sensor. The chosen genera include mosquito species that have a major impact on public health in many parts of the world. Five features were extracted from each recording to form balanced datasets and used for the training and evaluation of five different machine learning algorithms to achieve the best model for mosquito classification.

Results

The best accuracy results achieved using machine learning were: 94.2% for genus classification, 99.4% for sex classification of Aedes, and 100% for sex classification of Culex. The best algorithms and features were deep neural network with spectrogram for genus classification and gradient boosting with Mel Frequency Cepstrum Coefficients among others for sex classification of either genus.

Conclusions

To our knowledge, this is the first time that a sensor coupled to a standard mosquito suction trap has provided automatic classification of mosquito genus and sex with high accuracy using a large number of unique samples with class balance. This system represents an improvement of the state of the art in mosquito surveillance and encourages future use of the sensor for remote, real-time characterization of mosquito populations.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05324-5.

Continuous monitoring of aerial density and circadian rhythms of flying insects in a semi-urban environment

Although small in size, insects are a quintessential part of terrestrial ecosystems due to their large number and diversity. While captured insects can be thoroughly studied in laboratory conditions, their population dynamics and abundance in the wild remain largely unknown due to the lack of accurate methodologies to count them. Here, we present the results of a field experiment where the activity of insects has been monitored continuously over 3 months using an entomological stand-off optical sensor (ESOS). Because its near-infrared laser is imperceptible to insects, the instrument provides an unbiased and absolute measurement of the aerial density (flying insect/m3) with a temporal resolution down to the minute. Multiple clusters of insects are differentiated based on their wingbeat frequency and ratios between wing and body optical cross-sections. The collected data allowed for the study of the circadian rhythm and daily activities as well as the aerial density dynamic over the whole campaign for each cluster individually. These measurements have been compared with traps for validation of this new methodology. We believe that this new type of data can unlock many of the current limitations in the collection of entomological data, especially when studying the population dynamics of insects with large impacts on our society, such as pollinators or vectors of infectious diseases.

Recent advances in the remote sensing of insects

Remote sensing has revolutionised many aspects of ecological research, enabling spatiotemporal data to be collected in an efficient and highly automated manner. The last two decades have seen phenomenal growth in capabilities for high-resolution remote sensing that increasingly offers opportunities to study small, but ecologically important organisms, such as insects. Here we review current applications for using remote sensing within entomological research, highlighting the emerging opportunities that now arise through advances in spatial, temporal and spectral resolution. Remote sensing can be used to map environmental variables, such as habitat, microclimate and light pollution, capturing data on topography, vegetation structure and composition, and luminosity at spatial scales appropriate to insects. Such data can also be used to detect insects indirectly from the influences that they have on the environment, such as feeding damage or nest structures, whilst opportunities for directly detecting insects are also increasingly available. Entomological radar and light detection and ranging (LiDAR), for example, are transforming our understanding of aerial insect abundance and movement ecology, whilst ultra-high spatial resolution drone imagery presents tantalising new opportunities for direct observation. Remote sensing is rapidly developing into a powerful toolkit for entomologists, that we envisage will soon become an integral part of insect science.

Identification of Flying Insects in the Spatial, Spectral, and Time Domains with Focus on Mosquito Imaging

Insects constitute a very important part of the global ecosystem and include pollinators, disease vectors, and agricultural pests, all with pivotal influence on society. Monitoring and control of such insects has high priority, and automatic systems are highly desirable. While capture and analysis by biologists constitute the gold standard in insect identification, optical and laser techniques have the potential for high-speed detection and automatic identification based on shape, spectroscopic properties such as reflectance and fluorescence, as well as wing-beat frequency analysis. The present paper discusses these approaches, and in particular presents a novel method for automatic identification of mosquitos based on image analysis, as the insects enter a trap based on a combination of chemical and suction attraction. Details of the analysis procedure are presented, and selectivity is discussed. An accuracy of 93% is achieved by our proposed method from a data set containing 122 insect images (mosquitoes and bees). As a powerful and cost-effective method, we finally propose the combination of imaging and wing-beat frequency analysis in an integrated instrument.

Bark beetles as lidar targets and prospects of photonic surveillance

Forestry is raising concern about the outbreaks of European spruce bark beetle, Ips typographus, causing extensive damage to the spruce forest and timber values. Precise monitoring of these beetles is a necessary step towards preventing outbreaks. Current commercial monitoring methods are catch-based and lack in both temporal and spatial resolution. In this work, light scattering from beetles is characterized, and the feasibility of entomological lidar as a tool for long-term monitoring of bark beetles is explored. Laboratory optical properties, wing thickness, and wingbeat frequency of bark beetles are reported, and these parameters can infer target identity in lidar data. Lidar results from a Swedish forest with controlled bark beetle release event are presented. The capability of lidar to simultaneously monitor both insects and a pheromone plume mixed with chemical smoke governing the dispersal of many insects is demonstrated. In conclusion, entomological lidar is a promising tool for monitoring bark beetles.

A Review of Insect Monitoring Approaches with Special Reference to Radar Techniques

Drastic declines in insect populations are a vital concern worldwide. Despite widespread insect monitoring, the significant gaps in the literature must be addressed. Future monitoring techniques must be systematic and global. Advanced technologies and computer solutions are needed. We provide here a review of relevant works to show the high potential for solving the aforementioned problems. Major historical and modern methods of insect monitoring are considered. All major radar solutions are carefully reviewed. Insect monitoring with radar is a well established technique, but it is still a fast-growing topic. The paper provides an updated classification of insect radar sets. Three main groups of insect radar solutions are distinguished: scanning, vertical-looking, and harmonic. Pulsed radar sets are utilized for all three groups, while frequency-modulated continuous-wave (FMCW) systems are applied only for vertical-looking and harmonic insect radar solutions. This work proves the high potential of radar entomology based on the growing research interest, along with the emerging novel setups, compact devices, and data processing approaches. The review exposes promising insect monitoring solutions using compact radar instruments. The proposed compact and resource-effective setups can be very beneficial for systematic insect monitoring.

Global Open Data Remote Sensing Satellite Missions for Land Monitoring and Conservation: A Review

The application of global open data remote sensing satellite missions in land monitoring and conservation studies is in the state of rapid growth, ensuring an observation with high spatial and spectral resolution over large areas. The purpose of this study was to provide a review of the most important global open data remote sensing satellite missions, current state-of-the-art processing methods and applications in land monitoring and conservation studies. Multispectral (Landsat, Sentinel-2, and MODIS), radar (Sentinel-1), and digital elevation model missions (SRTM, ASTER) were analyzed, as the most often used global open data satellite missions, according to the number of scientific research articles published in Web of Science database. Processing methods of these missions’ data consisting of image preprocessing, spectral indices, image classification methods, and modelling of terrain topographic parameters were analyzed and demonstrated. Possibilities of their application in land cover, land suitability, vegetation monitoring, and natural disaster management were evaluated, having high potential in broad use worldwide. Availability of free and complementary satellite missions, as well as the open-source software, ensures the basis of effective and sustainable land use management, with the prerequisite of the more extensive knowledge and expertise gathering at a global scale.

Insect flight velocity measurement with a CW near-IR Scheimpflug lidar system

Flight velocity measurement is an important aspect of insect research that can aid insect identification and facilitate studies and monitoring of insect movements. We propose a novel scheme for the 1-D flight velocity measurement of insects, based on a near-IR Scheimpflug lidar system. We implement this new technique and apply it to study insects at the Salter Research Farm, Robertson County, Texas. The resolution property perpendicular to the probing direction of the Scheimpflug lidar system is explored and reveals the capability of retrieving the velocity component normal to the probing direction of insects passing through the field of view of our system. We observe a shift in wingbeat frequency, which indicates the presence of new insect species during the multi-day measurement. The study on 1-D flight velocity reveals a net directional movement of insects, providing supportive evidence of the arrival of a new species.

Lidar reveals activity anomaly of malaria vectors during pan-African eclipse

Yearly, a quarter billion people are infected and a half a million killed by the mosquito-borne disease malaria. Lack of real-time observational tools for continuously assessing the unperturbed mosquito flight activity in situ limits progress toward improved vector control. We deployed a high-resolution entomological lidar to monitor a half-kilometer static transect adjacent to a Tanzanian village. We evaluated one-third million insect observations during five nights, four days, and one annular solar eclipse. We demonstrate in situ lidar classification of several insect families and their sexes based on their modulation signatures. We were able to compare the fine-scale spatiotemporal activity patterns of malaria vectors during ordinary days and an eclipse to disentangle phototactic activity patterns from the circadian mechanism. We observed an increased insect activity during the eclipse attributable to mosquitoes. These unprecedented findings demonstrate how lidar-based monitoring of distinct mosquito activities could advance our understanding of vector ecology.

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

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.

Multiband modulation spectroscopy for the determination of sex and species of mosquitoes in flight

We present a dual-wavelength polarimetric measurement method to distinguish species and sexes of disease transmitting mosquitoes in flight. By measuring co- and de-polarized backscattered light at 808 and 1550 nm, the degree of linear polarization, wingbeat frequency, reflectance, spectral ratio and glossiness of mosquitoes can be retrieved. Body and wing contributions to these signals can be separated. Whereas the optical cross section is sensitive to the aspect of observation, thus the heading direction of the insect in flight, we demonstrate that polarimetric- and spectral-band ratios are largely invariant to the aspect of observation. We show that wing glossiness, as well as wing- and body-spectral ratios are particularly efficient in distinguishing Anopheles coluzzii and Anopheles arabiensis, 2 closely related species of malaria vectors. Spectral and polarimetric ratios relate to microstructural and melanization features of the wing and body of these species. We conclude that multiband modulation spectroscopy is a useful expansion of the parameter space that can be used to improve the specificity of entomological lidars.

Can the narrow red bands of dragonflies be used to perceive wing interference patterns?

Despite numerous studies of selection on position and number of spectral vision bands, explanations to the function of narrow spectral bands are lacking. We investigate dragonflies (Odonata), which have the narrowest spectral bands reported, in order to investigate what features these narrow spectral bands may be used to perceive. We address whether it is likely that narrow red bands can be used to identify conspecifics by the optical signature from wing interference patterns (WIPs). We investigate the optical signatures of Odonata wings using hyperspectral imaging, laser profiling, ellipsometry, polarimetric modulation spectroscopy, and laser radar experiments. Based on results, we estimate the prospects for Odonata perception of WIPs to identify conspecifics in the spectral, spatial, intensity, polarization, angular, and temporal domains. We find six lines of evidence consistent with an ability to perceive WIPs. First, the wing membrane thickness of the studied Odonata is 2.3 μm, coinciding with the maximal thickness perceivable by the reported bandwidth. Second, flat wings imply that WIPs persist from whole wings, which can be seen at a distance. Third, WIPs constitute a major brightness in the visual environment only second after the solar disk. Fourth, WIPs exhibit high degree of polarization and polarization vision coincides with frontal narrow red bands in Odonata. Fifth, the angular light incidence on the Odonata composite eye provides all prerequisites for direct assessment of the refractive index which is associated with age. Sixth, WIPs from conspecifics in flight make a significant contribution even to the fundamental wingbeat frequency within the flicker fusion bandwidth of Odonata vision. We conclude that it is likely that WIPs can be perceived by the narrow red bands found in some Odonata species and propose future behavioral and electrophysiological tests of this hypothesis.

Inelastic hyperspectral lidar for aquatic ecosystems monitoring and landscape plant scanning test

We have developed an aquatic inelastic hyperspectral lidar with unrestricted focal-depth and enough sensitivity and spatio-temporal resolution to detect and resolve position and behavior of individual sub-millimeter aquatic organisms. We demonstrate ranging with monitoring of elastic echoes, water Raman signals and fluorescence from chlorophyllbearing phytoplankton and dye tagged organisms. The system is based on a blue CW diode laser and a Scheimpflug optical arrangement.

Insect remote sensing using a polarization sensitive cw lidar system in chinese rice fields

A joint Chinese-Swedish field campaign of Scheimpflug continuous-wave lidar monitoring of rice-field flying pest insects was pursued in very hot July weather conditions close to Guangzhou, China. The occurrence of insects, birds and bats with almost 200 hours of round-the-clock polarization-sensitive recordings was studied. Wing-beat frequency recordings and depolarization properties were used for target classification. Influence of weather conditions on the flying fauna was also investigated.

Short-Wave infrared atmospheric scheimpflug lidar

Atmospheric dual-band Scheimpflug lidar is demonstrated at 980 and 1550 nm. Signals are compared during three weather conditions, and the spatio-temporal resolution of the atmospheric structure is considered. The potential for aerosol classification is evaluated, and future directions are discussed.

Optical remote sensing for monitoring flying mosquitoes, gender identification and discussion on species identification

Mosquito-borne diseases are a major challenge for Human health as they affect nearly 700 million people every year and result in over 1 million deaths. Reliable information on the evolution of population and spatial distribution of key insects species is of major importance in the development of eco-epidemiologic models. This paper reports on the remote characterization of flying mosquitoes using a continuous-wave infrared optical remote sensing system. The system is setup in a controlled environment to mimic long-range lidars, mosquitoes are free flying at a distance of ~ 4 m from the collecting optics. The wing beat frequency is retrieved from the backscattered light from mosquitoes transiting through the laser beam. A total of 427 transit signals have been recorded from three mosquito species, males and females. Since the mosquito species and gender are known a priori, we investigate the use of wing beat frequency as the sole predictor variable for two Bayesian classifications: gender alone (two classes) and species/gender (six classes). The gender of each mosquito is retrieved with a 96.5% accuracy while the species/gender of mosquitoes is retrieved with a 62.3% accuracy. Known to be an efficient mean to identify insect family, we discuss the limitations of using wing beat frequency alone to identify insect species.

Observations of movement dynamics of flying insects using high resolution lidar

Insects are fundamental to ecosystem functioning and biodiversity, yet the study of insect movement, dispersal and activity patterns remains a challenge. Here we present results from a novel high resolution laser-radar (lidar) system for quantifying flying insect abundance recorded during one summer night in Sweden. We compare lidar recordings with data from a light trap deployed alongside the lidar. A total of 22808 insect were recorded, and the relative temporal quantities measured matched the quantities recorded with the light trap within a radius of 5 m. Lidar records showed that small insects (wing size <2.5 mm(2) in cross-section) moved across the field and clustered near the light trap around 22:00 local time, while larger insects (wing size >2.5 mm(2) in cross-section) were most abundant near the lidar beam before 22:00 and then moved towards the light trap between 22:00 and 23:30. We could distinguish three insect clusters based on morphology and found that two contained insects predominantly recorded above the field in the evening, whereas the third was formed by insects near the forest at around 21:30. Together our results demonstrate the capability of lidar for distinguishing different types of insect during flight and quantifying their movements.

Realistic Instrumentation Platform for Active and Passive Optical Remote Sensing

We describe the development of a novel versatile optical platform for active and passive remote sensing of environmental parameters. Applications include assessment of vegetation status and water quality. The system is also adapted for ecological studies, such as identification of flying insects including agricultural pests. The system is based on two mid-size amateur astronomy telescopes, continuous-wave diode lasers at different wavelengths ranging from violet to the near infrared, and detector facilities including quadrant photodiodes, two-dimensional and line scan charge-coupled device cameras, and a compact digital spectrometer. Application examples include remote Ramanlaser-induced fluorescence monitoring of water quality at 120 m distance, and insect identification at kilometer ranges using the recorded wing beat frequency and its spectrum of overtones. Because of the low cost this developmental platform is very suitable for advanced research projects in developing countries and has, in fact, been multiplied during hands-on workshops and is now being used by a number of groups at African universities.