Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Multi-sensor tracking reveals the extent of nocturnal migration in landbirds.

Current biology : CB·2026

Same author

Differential responses to photoperiod in juveniles of two migratory songbird species.

The Journal of experimental biology·2026

Same author

Robust and diverse multidimensional statistical moments in dual-band entomological lidar for improved real-time insect monitoring.

The Journal of experimental biology·2026

Same author

Moonlight drives the energy balance and annual cycle of a nocturnal forager.

Science advances·2026

Same author

Flower color variation in Digitalis purpurea: Pollination and soil influences across native and introduced populations.

American journal of botany·2026

Same author

Flight performance of great cormorants Phalacrocorax carbo sinensis suggests sufficient muscle capacity for adaptive speed adjustment.

The Journal of experimental biology·2026

Search research articles

Related Experiment Video

Updated: Jun 9, 2026

Flying Insect Detection and Classification with Inexpensive Sensors

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

Feasibility study: fluorescence lidar for remote bird classification.

Mikkel Brydegaard¹, Patrik Lundin, Zuguang Guan

¹Atomic Physics Division, Lund University, P.O. Box 118, SE-221 00 Lund, Sweden. mikkel.brydegaard@fysik.lth.se

|August 25, 2010

Summary

We developed a new fluorescence lidar method for remote bird classification. This technique aids in understanding bird migration and virus spread, especially for night-flying species.

More Related Videos

Laser-Induced Fluorescence Emission (L.I.F.E.) as Novel Non-Invasive Tool for In-Situ Measurements of Biomarkers in Cryospheric Habitats

Laser-Induced Fluorescence Emission (L.I.F.E.) as Novel Non-Invasive Tool for In-Situ Measurements of Biomarkers in Cryospheric Habitats

Published on: October 26, 2019

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

Related Experiment Videos

Last Updated: Jun 9, 2026

Flying Insect Detection and Classification with Inexpensive Sensors

Flying Insect Detection and Classification with Inexpensive Sensors

Published on: October 15, 2014

Laser-Induced Fluorescence Emission (L.I.F.E.) as Novel Non-Invasive Tool for In-Situ Measurements of Biomarkers in Cryospheric Habitats

Laser-Induced Fluorescence Emission (L.I.F.E.) as Novel Non-Invasive Tool for In-Situ Measurements of Biomarkers in Cryospheric Habitats

Published on: October 26, 2019

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring

Published on: October 24, 2025

Area of Science:

Ecology
Remote Sensing
Biophysics

Background:

Bird classification is crucial for ecological studies, including migration patterns and disease transmission.
Remote sensing techniques offer non-invasive methods for wildlife monitoring.
Fluorescence properties of biological materials can be used for identification.

Purpose of the Study:

To introduce and validate an eye-safe fluorescence lidar method for remote bird classification.
To investigate the relationship between plumage reflectance and fluorescence.
To demonstrate the applicability of the method for studying bird migration and disease ecology.

Main Methods:

Utilized eye-safe fluorescence lidar technology for remote sensing of birds.
Conducted laboratory measurements of plumage reflectance and fluorescence.
Performed test-range measurements and analyzed in-flight lidar returns.
Investigated fluorescence quenching mechanisms.

Main Results:

Established a correlation between plumage reflectance and fluorescence.
Presented successful laboratory and test-range measurements.
Demonstrated the collection of in-flight lidar returns from birds.
Quantified fluorescence quenching effects relevant to lidar signals.

Conclusions:

The developed fluorescence lidar method is effective for remote bird classification.
This technique is suitable for studying nocturnal and high-altitude migrating species.
The findings have implications for avian migration research and understanding global virus transmission patterns.