A neural network aerosol-typing algorithm based on lidar data
A neural network aerosol-typing algorithm based on lidar data is a scholarly work, published in 2018 in ''Atmospheric Chemistry and Physics''. The main subjects of the publication include methane emissions, lidar, multispectral image, computer science, data set, remote sensing, artificial neural network, environmental science, aerosol, meteorology, and algorithm. Blind tests on EARLINET data samples showed the capability of NATALI to retrieve the aerosol type from a large variety of data, with different levels of quality and physical content..