Lidar Applications in Insect Ecology and Monitoring

Lidar systems, which employ laser pulses to detect and characterise flying insects, have emerged as powerful tools for ecological research and population monitoring. By capturing backscattered light from insect bodies and wings, lidar enables non-invasive measurement of abundance, biomass and movement dynamics across spatial and temporal scales inaccessible to traditional trapping methods. Advances in sensor technology and data analysis now allow continuous high-resolution surveys that link insect activity patterns to environmental drivers such as temperature, humidity and wind speed. Integration with machine-learning classifiers further permits real-time discrimination of functional groups and pest versus beneficial species, underpinning applications in conservation, pest management and pollination ecology. Collectively, lidar approaches are transforming our capacity to observe insect population trends, elucidate predator–prey interactions and forecast ecological responses to global change.

Research from Nature Portfolio

A year-long field campaign deployed a near-infrared entomological optical sensor to derive aerial density and biomass density of flying insects with one-minute resolution. The study revealed seasonal peaks in abundance above 12.5 °C and quantified the influence of relative humidity and wind speed on insect activity, demonstrating the capacity of photonic sensors to generate high-frequency ecological time series over extended periods. Another investigation evaluated optical remote sensors coupled with machine-learning classifiers to distinguish pest and beneficial insects in oilseed rape crops. With over 80 percent classification accuracy achieved across ten thousand flight records, this approach showcases the potential for precision agriculture by guiding spatially targeted pesticide applications. Earlier work introduced a high-resolution lidar system for tracking insect movement dynamics over a nocturnal landscape. By comparing lidar returns to light-trap data, researchers distinguished morphological clusters and documented temporal shifts in flight locations, laying the groundwork for mechanistic studies of dispersal and swarming behaviour.

Lidar Applications in Insect Ecology and Monitoring publication trend

The graph below shows the total number of articles in lidar applications in insect ecology and monitoring across all publications each year (not limited to Nature Index journals).

Technical terms

Lidar: Remote sensing technique using laser pulses to detect and range objects by measuring backscattered light.

Photonic sensor: Device that captures light signals emitted or reflected by flying insects for ecological monitoring.

Biomass density: Mass of insect material per unit volume of air, often expressed in milligrams per cubic metre.

Wing-beat frequency: Rate at which an insect’s wings oscillate, used as a discriminative signal in optical detection.

Changepoint detection: Statistical method for identifying shifts in time-series data without prior labelling.

Scheimpflug Lidar: High-resolution lidar configuration employing a tilted focal plane to maintain sharp imaging across a scan.

References

1. Monitoring the abundance of flying insects and atmospheric conditions during a 9-month campaign using an entomological optical sensor. Scientific Reports (2023).
2. Advances in automatic identification of flying insects using optical sensors and machine learning. Scientific Reports (2021).
3. Observations of movement dynamics of flying insects using high resolution lidar. Scientific Reports (2016).
4. Comparison of Supervised Learning and Changepoint Detection for Insect Detection in Lidar Data. Remote Sensing (2023).
5. The batbirdbug battle: daily flight activity of insects and their predators over a rice field revealed by high-resolution Scheimpflug Lidar. Royal Society Open Science (2018).
6. Towards Quantitative Optical Cross Sections in Entomological Laser Radar – Potential of Temporal and Spherical Parameterizations for Identifying Atmospheric Fauna. PLOS ONE (2015).