35 largest clusters (HCA, DoLP dataset).

<div><p>Identifying flying insects is a significant challenge for biologists. Entomological lidar offers a unique solution, enabling rapid identification and classification in field settings. No other method can match its speed and efficiency in identifying insects in flight. This non-in...

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Bibliographic Details
Main Author:	Dolores Bernenko (16528426) (author)
Other Authors:	Meng Li (79487) (author), Hampus Månefjord (18694803) (author), Samuel Jansson (5023679) (author), Anna Runemark (2929635) (author), Carsten Kirkeby (405314) (author), Mikkel Brydegaard (785875) (author)
Published:	2024
Subjects:	Physiology Biotechnology Evolutionary Biology Ecology Developmental Biology Biological Sciences not elsewhere classified wing beat frequency partially predicted even lidar polarization bands insect diversity estimation informing conservation planning gaussian mixture model entomological lidar offers enabling rapid identification discernible signal types daily activity patterns current photonic sensors assessing insect biodiversity polarimetric properties could physical properties unpolarized light unique solution species richness species represented spatial distribution significant challenge reach tens minor improvement meter transect lower bound intrusive tool identifying insects field settings existing insects evaluating efforts differentiating species currently limited clusters correlate clustered observations analysis shows algorithm sophistication 533 observations
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35 largest clusters (HCA, DoLP dataset).

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