Possibilities of IPDA spaceborne lidar and neural networks for measuring methane concentration

A. Ya. Sukhanov; G. G. Matvienko

doi:10.1117/12.2538845

18 December 2019 Possibilities of IPDA spaceborne lidar and neural networks for measuring methane concentration

A. Ya. Sukhanov, G. G. Matvienko

Proceedings Volume 11208, 25th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics; 112082U (2019) https://doi.org/10.1117/12.2538845
Event: XXV International Symposium, Atmospheric and Ocean Optics, Atmospheric Physics, 2019, Novosibirsk, Russian Federation

Abstract

The possibilities of retrieving the mean relative concentration of methane using pseudo-inverse matrices, fully connected and convolutional neural networks based on signals from the Earth received by a 450 km orbit space-based lidar are considered. It is shown that the random error of methane concentration retrieving for lidar with laser pulse energy of 9 mJ and repetition rate 20 Hz, receiving system size of 68 cm, resolution of 50-60 km is not higher than 30 ppb.

Citation Download Citation

A. Ya. Sukhanov and G. G. Matvienko "Possibilities of IPDA spaceborne lidar and neural networks for measuring methane concentration", Proc. SPIE 11208, 25th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 112082U (18 December 2019); https://doi.org/10.1117/12.2538845

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