Aerosol type classification with machine learning techniques applied to multiwavelength lidar data from EARLINET

<p>Aerosol typing is essential for understanding atmospheric composition and its impact on the climate. Lidar-based aerosol typing has been often addressed with manual classification using optical property ranges. However, few works addressed it using automated classification with machine learning (...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	A. del Águila, P. Ortiz-Amezcua, S. Tabik, J. A. Bravo-Aranda, S. Fernández-Carvelo, L. Alados-Arboledas
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	Copernicus Publications 2025-10-01
Sarja:	Atmospheric Chemistry and Physics
Linkit:	https://acp.copernicus.org/articles/25/12549/2025/acp-25-12549-2025.pdf
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