8 citations as recorded by crossref.

1. Aerosol Absorption Over Land Derived From the Ultra-Violet Aerosol Index by Deep Learning J. Sun et al. 10.1109/JSTARS.2021.3108669
2. Application of airborne and spaceborne hyperspectral imaging techniques for atmospheric research: past, present, and future M. Calin et al. 10.1080/05704928.2020.1774381
3. Using machine learning to derive cloud condensation nuclei number concentrations from commonly available measurements A. Nair & F. Yu 10.5194/acp-20-12853-2020
4. The Spectral Nature of Earth’s Reflected Radiation: Measurement and Science Applications G. Stephens et al. 10.3389/frsen.2021.664291
5. MODIS aerosol optical depth retrieval based on random forest approach T. Liang et al. 10.1080/2150704X.2020.1842540
6. Use of Machine Learning to Reduce Uncertainties in Particle Number Concentration and Aerosol Indirect Radiative Forcing Predicted by Climate Models F. Yu et al. 10.1029/2022GL098551
7. Estimation of Aerosol Optical Depth at 30 m Resolution Using Landsat Imagery and Machine Learning T. Liang et al. 10.3390/rs14051053
8. A physical knowledge-based machine learning method for near-real-time dust aerosol properties retrieval from the Himawari-8 satellite data J. Li et al. 10.1016/j.atmosenv.2022.119098