Analysis of predictor variables for mosquito species identification from dual-wavelength polarization-sensitive lidar measurements

Adrien P. Genoud; Roman Basistyy; Gregory M. Williams; Benjamin P. Thomas

doi:10.1117/12.2323432

24 October 2018 Analysis of predictor variables for mosquito species identification from dual-wavelength polarization-sensitive lidar measurements

Adrien P. Genoud, Roman Basistyy, Gregory M. Williams, Benjamin P. Thomas

Author Affiliations +

Proceedings Volume 10779, Lidar Remote Sensing for Environmental Monitoring XVI; 107790O (2018) https://doi.org/10.1117/12.2323432
Event: SPIE Asia-Pacific Remote Sensing, 2018, Honolulu, Hawaii, United States

Abstract

Mosquito-borne diseases are a major challenge for Human health as they affect nearly 700 million people every year. Monitoring insects is generally done through trapping methods that are tedious to set up, costly and present scientific biases. Entomological lidars are a potential solution to remotely count and identify mosquito species and gender in realtime. In this contribution, a dual-wavelength polarization sensitive lidar is used in laboratory conditions to retrieve the wingbeat frequency as well as optical properties of flying mosquitoes transiting through the laser beam. From the lidar signals, predictive variables are retrieved and used in a Bayesian classification. This paper focuses on determining the relative importance of the predictive variables used in the classification. Results show a strong dominance of the wingbeat frequency, the impact of predictive variables based on depolarization and backscattering ratios are discussed, showing a significant increase in classification accuracy.

Citation Download Citation

Adrien P. Genoud, Roman Basistyy, Gregory M. Williams, and Benjamin P. Thomas "Analysis of predictor variables for mosquito species identification from dual-wavelength polarization-sensitive lidar measurements", Proc. SPIE 10779, Lidar Remote Sensing for Environmental Monitoring XVI, 107790O (24 October 2018); https://doi.org/10.1117/12.2323432

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available