| Issue |
E3S Web Conf.
Volume 223, 2020
Regional Problems of Earth Remote Sensing (RPERS 2020)
|
|
|---|---|---|
| Article Number | 03013 | |
| Number of page(s) | 4 | |
| Section | Monitoring of the Environment, Natural and Anthropogenic Objects and Phenomena | |
| DOI | https://doi.org/10.1051/e3sconf/202022303013 | |
| Published online | 21 December 2020 | |
Automated multi-classifier recognition of atmospheric turbulent structures obtained by Doppler lidar
1 University of Littoral Cote d’Opale, Laboratory for Physico-Chemistry of the Atmosphere, Dunkerque, France
2 Institute of Numerical Mathematics of Russian Academy of Sciences, Moscow, Russia
* Corresponding author: anton.sokolov@univ-littoral.fr
We present algorithms and results of automated processing of LiDAR measurements obtained during VEGILOT measuring campaign in Paris in autumn 2014 in order to study horizontal turbulent atmospheric regimes on urban scales. To process images obtained by horizontal atmospheric scanning using Doppler LiDAR, the method is proposed based on texture analysis and classification using supervised machine learning algorithms. The results of the parallel classification by various classifiers were combined using the majority voting strategy. The obtained estimates of accuracy demonstrate the efficiency of the proposed method for solving the problem of remote sensing of regional-scale turbulent patterns in the atmosphere.
© The Authors, published by EDP Sciences, 2020
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