Robust and diverse multidimensional statistical moments in dual-band entomological lidar for improved real-time insect monitoring
(2026) In The Journal of experimental biology 229(11).- Abstract
As some insect groups are declining at alarming rates, accurate and automated insect monitoring is needed to prioritize habitats for conservation. The dual-band entomological Scheimpflug lidar technique is a promising candidate method for real-time insect monitoring: it allows the detection of thousands of flying insects per day at high temporal and spatial resolutions. The signals contain a plethora of properties which can be assigned to flight heading- and species-specific clues which may improve classification. Here, we introduce a systematic approach to robust dimensionality reduction of entomological lidar range-time intensity matrices (time and range, 2D) of observations, into time dependent vectors (1D) and scalar values (0D)... (More)
As some insect groups are declining at alarming rates, accurate and automated insect monitoring is needed to prioritize habitats for conservation. The dual-band entomological Scheimpflug lidar technique is a promising candidate method for real-time insect monitoring: it allows the detection of thousands of flying insects per day at high temporal and spatial resolutions. The signals contain a plethora of properties which can be assigned to flight heading- and species-specific clues which may improve classification. Here, we introduce a systematic approach to robust dimensionality reduction of entomological lidar range-time intensity matrices (time and range, 2D) of observations, into time dependent vectors (1D) and scalar values (0D) which encode features related to the flight heading and species characteristics. Using this single-night dataset as a case study, we show that dual-band parameters not only confirm expected patterns of average insect melanization but also enable exploration of signal diversity such as insects that display distinct spectral signatures.
(Less)
- author
- organization
-
- Lund Laser Centre, LLC
- LTH Profile Area: Photon Science and Technology
- Combustion Physics
- Sensory Biology
- Lund Vision Group (research group)
- LU Profile Area: Light and Materials
- Biodiversity and Evolution
- Speciation, Adaptation and Coevolution (research group)
- BECC: Biodiversity and Ecosystem services in a Changing Climate
- LTH Profile Area: Aerosols
- publishing date
- 2026-06-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Biodiversity, Entomological lidar, Remote sensing, Statistical moments
- in
- The Journal of experimental biology
- volume
- 229
- issue
- 11
- publisher
- The Company of Biologists Ltd
- external identifiers
-
- pmid:42093572
- scopus:105040755895
- ISSN
- 1477-9145
- DOI
- 10.1242/jeb.251761
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2026. Published by The Company of Biologists.
- id
- c2e0862f-77e7-4f9e-a8c5-a7a809f50dbd
- date added to LUP
- 2026-06-10 12:04:19
- date last changed
- 2026-06-17 03:14:36
@article{c2e0862f-77e7-4f9e-a8c5-a7a809f50dbd,
abstract = {{<p>As some insect groups are declining at alarming rates, accurate and automated insect monitoring is needed to prioritize habitats for conservation. The dual-band entomological Scheimpflug lidar technique is a promising candidate method for real-time insect monitoring: it allows the detection of thousands of flying insects per day at high temporal and spatial resolutions. The signals contain a plethora of properties which can be assigned to flight heading- and species-specific clues which may improve classification. Here, we introduce a systematic approach to robust dimensionality reduction of entomological lidar range-time intensity matrices (time and range, 2D) of observations, into time dependent vectors (1D) and scalar values (0D) which encode features related to the flight heading and species characteristics. Using this single-night dataset as a case study, we show that dual-band parameters not only confirm expected patterns of average insect melanization but also enable exploration of signal diversity such as insects that display distinct spectral signatures.</p>}},
author = {{Dreyer, David and Li, Meng and Månefjord, Hampus and Yamoa, Assoumou Saint Doria and Gbogbo, Yatana Adolphe and Müller, Lauro and Runemark, Anna and Kouakou, Benoit Kouassi and Boateng, Rabbi and Huzortey, Andrew Atiogbe and Zoueu, Jérémie T. and Anderson, Benjamin and Brydegaard, Mikkel}},
issn = {{1477-9145}},
keywords = {{Biodiversity; Entomological lidar; Remote sensing; Statistical moments}},
language = {{eng}},
month = {{06}},
number = {{11}},
publisher = {{The Company of Biologists Ltd}},
series = {{The Journal of experimental biology}},
title = {{Robust and diverse multidimensional statistical moments in dual-band entomological lidar for improved real-time insect monitoring}},
url = {{http://dx.doi.org/10.1242/jeb.251761}},
doi = {{10.1242/jeb.251761}},
volume = {{229}},
year = {{2026}},
}
