Hampus Månefjord, Assoumou Saint-Doria Yamoa, Yatana Adolphe Gbogbo, Lauro Müller, Anna Runemark, Benoit Kouassi Kouakou, Rabbi Boateng, Andrew Atiogbe Huzortey, Isaac Kwame Badu, Niklas Wahlberg, Mikkel Brydegaard, Jérémie T. Zoueu, Benjamin Anderson & Meng Li
10.1038/s41598-025-05200-z

Stratification of insect diversity and daily activity patterns in the West African virgin forest Taï assessed by entomological Lidar

This study used Lidar technology, alongside traditional trapping, to non-destructively explore insect diversity within the canopy of the Taï virgin forest in Côte d’Ivoire. The research found stratified patterns of insect activity, with Lidar signals revealing that different insect communities were active at different heights and times of the day. By correlating these signals with the optical properties of captured insects, the study shows that Lidar is a promising tool for continuously and non-invasively assessing insect biodiversity in complex ecosystems.

Meng Li , Hampus Månefjord , Julio Hernandez, Lauro Müller, Christian Brackmann , Aboma Merdasa, Carsten Kirkeby, Mengistu Dawit Bulo, Rickard Ignell and Mikkel Brydegaard
10.1177/00037028251341317

Deadliest Animals with the Thinnest Wings: Near-Infrared Properties of Tropical Mosquitoes

To better monitor mosquitoes that transmit diseases like malaria and Zika, this study developed a spectral reflectance model for remote classification. Using hyperspectral imaging on mosquitoes of different species, sexes, ages, and gravidity states, we determined key parameters like wing thickness (a record-thin 174 nm), melanin, and water pathlengths with high accuracy. Crucially, we found that a mosquito’s orientation has a minimal effect on its shortwave infrared spectra. These results show the potential for spectral sensors and lidars to remotely retrieve micro- and nanoscopic mosquito features, leading to more specific vector monitoring.

Coherent Backscattering from Free-Flying Insects: Implications for Remote Species Identification

Meng Li| Division Of Combustion Physics | Department Of Physics | Lund University | 2024

The decline in insect populations necessitates better monitoring tools. Conventional methods are labor-intensive and lack real-time data. Remote sensing offers a solution, but current techniques have limitations in species differentiation. To address this, entomological lidar has been developed, utilizing the Scheimpflug principle. This research investigates how insect optical properties can enhance their identification through lidar. It explores wing reflectance, interference patterns, surface roughness, and polarimetry. Methodologies like dual-band and hyperspectral lidar are also being investigated. Entomological lidar, with photonic techniques, can transform insect monitoring, improving pest control, biodiversity studies, and our understanding of these vital creatures.

Toward Accessible Biophotonics: Instrumentation for Insect and Vegetation Applications

Hampus Månefjord | Division Of Combustion Physics | Department Of Physics | Lund University | 2024

This thesis focuses on the development and implementation of accessible biophotonic instruments for insect and vegetation studies. These include a novel six-dimensional camera that captures spatial, spectral, polarimetric, and goniometric information. This instrument analyzed malaria and Zika mosquito species, sex, age, and gravidity. Additionally, two hyperspectral lidars were created – one for fluorescence, enabling studies of chlorophyll response and monitoring tagged insects (e.g., stingless bees), and the other for elastic light, used for the first-ever remote wing thickness measurements of flying insects. Both lidars are unique in featuring 70 spectral bands.

Insects in the spotlight
photonic monitoring of bees and insect biodiversity

Klas Rydhmer | Department of Geosciences and Natural Resource Management | University of Copenhagen | 2023

This thesis presents a spatial model for honeybee monitoring using conventional entomological lidar, demonstrating good agreement with manual observations. It details the development of the new “Volito” sensor and correlates measured insect abundance with yellow water traps. The thesis explores a deep learning approach to feature extraction from recorded data, improving upon earlier models from the literature. Finally, it includes two draft manuscripts. The first attempts to correlate a sensor-based diversity metric with conventional monitoring methods in agricultural fields in Iowa, USA. The second focuses on protected areas in southern Scandinavia.

Entomological Lidar
Target Characterization and Field Applications

Samuel Jansson | Division Of Combustion Physics | Department Of Physics | Lund University | 2020

In this thesis work, peak numbers of more than a thousand insects per minute have been observed, resolved temporally and spatially at μs and cm scales, respectively, which is inconceivable with conventional entomological methods. Laboratory reference work and methodological development allow the quantification and classification of insect signals in-situ. Thereby, questions of significant ecological importance could be answered.

From Fauna to Flames Remote Sensing with Scheimpflug-Lidar

Elin Malmqvist | Faculty Of Engineering | Department Of Physics | Lund University | 2019

This thesis presents applications of the Scheimpflug Lidar (S-Lidar) method. The technique has been applied to combustion diagnostics on a scale of several meters as well as fauna detection and monitoring over distances of kilometers. Lidar or laser radar is a remote sensing technique where backscattering of laser light is detected with range resolution along the direction of the laser beam. It is an established method in e.g. atmospheric sensing where it is used to map and monitor gases and aerosols. In contrast to conventional Lidar, which uses a time-of-flight approach, Scheimpflug Lidar uses imaging to achieve range resolution. The laser beam transmitted from the Lidar system is sharply imaged onto a detector, resulting in range resolution along the sensor