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An automatic observation-based aerosol typing method for EARLINET

Autor
Papagiannopoulos, N.; Mona, L.; Amodeo, A.; D'Amico, G.; Comeron, A.; Rodriguez-Gomez, A.; Sicard, M.
Tipus d'activitat
Article en revista
Revista
Atmospheric chemistry and physics
Data de publicació
2018-11-06
Volum
18
Número
21
Pàgina inicial
15879
Pàgina final
15901
DOI
https://doi.org/10.5194/acp-18-15879-2018 Obrir en finestra nova
Projecte finançador
European natural airborne disaster information and coordination system for aviation
Repositori
http://hdl.handle.net/2117/125208 Obrir en finestra nova
URL
https://www.atmos-chem-phys.net/18/15879/2018/ Obrir en finestra nova
Resum
We present an automatic aerosol classification method based solely on the European Aerosol Research Lidar Network (EARLINET) intensive optical parameters with the aim of building a network-wide classification tool that could provide near-real-time aerosol typing information. The presented method depends on a supervised learning technique and makes use of the Mahalanobis distance function that relates each unclassified measurement to a predefined aerosol type. As a first step (training phase), a ...
Grup de recerca
RSLAB - Grup de Recerca en Teledetecció

Participants