7 citations as recorded by crossref.

1. Retrieval of aerosol optical depth from INSAT-3DR for accurate geostationary monitoring of regional and temporal aerosol dynamics C. Tandule et al. https://doi.org/10.1016/j.atmosenv.2025.121730
2. Unveiling diurnal aerosol layer height variability from space using deep learning Y. Fan et al. https://doi.org/10.1016/j.isprsjprs.2025.08.021
3. Correcting aerosol extinction coefficient vertical structure biases in GEOS-chem via a physics-informed transformer with physical mechanism diagnosis J. Xiong et al. https://doi.org/10.5194/acp-26-8225-2026
4. A hybrid physics-ML framework for aerosol optical depth retrieval from OCM-2 on Oceansat-2 satellite M. Gogoi et al. https://doi.org/10.1016/j.jqsrt.2026.110139
5. Artificial Intelligence in Sand and Dust Storm Research: A Systematic and Bibliometric Review (1990–2025) H. Anwer et al. https://doi.org/10.1016/j.atmosenv.2026.122387
6. Aerosol extinction coefficient estimation over the European troposphere and lower stratosphere using CALIOP profiles M. Kavosh & M. Satari https://doi.org/10.1016/j.atmosres.2025.108448
7. Impact comparison of different aerosol types on atmospheric correction of Landsat 8 over land S. Zhang et al. https://doi.org/10.5194/amt-19-5281-2026