Discrimination of Hover Fly Species and Sexes by Wing Interference Signals
(2023) In Advanced Science- Abstract
- Remote automated surveillance of insect abundance and diversity is poised to revolutionize insect decline studies. The study reveals spectral analysis of thin‐film wing interference signals (WISs) can discriminate free‐flying insects beyond what can be accomplished by machine vision. Detectable by photonic sensors, WISs are robust indicators enabling species and sex identification. The first quantitative survey of insect wing thickness and modulation through shortwave‐infrared hyperspectral imaging of 600 wings from 30 hover fly species is presented. Fringy spectral reflectance of WIS can be explained by four optical parameters, including membrane thickness. Using a Naïve Bayes Classifier with five parameters that can be retrieved... (More)
- Remote automated surveillance of insect abundance and diversity is poised to revolutionize insect decline studies. The study reveals spectral analysis of thin‐film wing interference signals (WISs) can discriminate free‐flying insects beyond what can be accomplished by machine vision. Detectable by photonic sensors, WISs are robust indicators enabling species and sex identification. The first quantitative survey of insect wing thickness and modulation through shortwave‐infrared hyperspectral imaging of 600 wings from 30 hover fly species is presented. Fringy spectral reflectance of WIS can be explained by four optical parameters, including membrane thickness. Using a Naïve Bayes Classifier with five parameters that can be retrieved remotely, 91% is achieved accuracy in identification of species and sexes. WIS‐based surveillance is therefore a potent tool for remote insect identification and surveillance. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/02191072-ccb5-43c6-be0b-b83eaa0de36d
- author
- Li, Meng LU ; Runemark, Anna LU ; Hernandez, Julio ; Rota, Jadranka LU ; Bygebjerg, Rune LU and Brydegaard, Mikkel LU
- organization
- publishing date
- 2023-10-18
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- insect, lidar, WIPs
- in
- Advanced Science
- publisher
- John Wiley & Sons Inc.
- external identifiers
-
- pmid:37847885
- scopus:85174283831
- ISSN
- 2198-3844
- DOI
- 10.1002/advs.202304657
- language
- English
- LU publication?
- yes
- id
- 02191072-ccb5-43c6-be0b-b83eaa0de36d
- alternative location
- https://onlinelibrary.wiley.com/doi/10.1002/advs.202304657
- date added to LUP
- 2023-10-18 19:15:53
- date last changed
- 2024-09-01 09:47:26
@article{02191072-ccb5-43c6-be0b-b83eaa0de36d, abstract = {{Remote automated surveillance of insect abundance and diversity is poised to revolutionize insect decline studies. The study reveals spectral analysis of thin‐film wing interference signals (WISs) can discriminate free‐flying insects beyond what can be accomplished by machine vision. Detectable by photonic sensors, WISs are robust indicators enabling species and sex identification. The first quantitative survey of insect wing thickness and modulation through shortwave‐infrared hyperspectral imaging of 600 wings from 30 hover fly species is presented. Fringy spectral reflectance of WIS can be explained by four optical parameters, including membrane thickness. Using a Naïve Bayes Classifier with five parameters that can be retrieved remotely, 91% is achieved accuracy in identification of species and sexes. WIS‐based surveillance is therefore a potent tool for remote insect identification and surveillance.}}, author = {{Li, Meng and Runemark, Anna and Hernandez, Julio and Rota, Jadranka and Bygebjerg, Rune and Brydegaard, Mikkel}}, issn = {{2198-3844}}, keywords = {{insect; lidar; WIPs}}, language = {{eng}}, month = {{10}}, publisher = {{John Wiley & Sons Inc.}}, series = {{Advanced Science}}, title = {{Discrimination of Hover Fly Species and Sexes by Wing Interference Signals}}, url = {{http://dx.doi.org/10.1002/advs.202304657}}, doi = {{10.1002/advs.202304657}}, year = {{2023}}, }