23 citations as recorded by crossref.

1. A novel approach of Landsat 8 imagery to predict PM2.5 concentrations in a south-eastern coastal city of China L. Yang https://doi.org/10.1088/1755-1315/619/1/012046
2. SCIATRAN software package (V4.6): update and further development of aerosol, clouds, surface reflectance databases and models L. Mei et al. https://doi.org/10.5194/gmd-16-1511-2023
3. Aerosol optical depth retrieval from the EarthCARE Multi-Spectral Imager: the M-AOT product N. Docter et al. https://doi.org/10.5194/amt-16-3437-2023
4. Properties of aerosol and surface derived from OLCI/Sentinel-3A using GRASP approach: Retrieval development and preliminary validation C. Chen et al. https://doi.org/10.1016/j.rse.2022.113142
5. Retrieval of Aerosol Optical Thickness in the Arctic Snow-Covered Regions Using Passive Remote Sensing: Impact of Aerosol Typing and Surface Reflection Model L. Mei et al. https://doi.org/10.1109/TGRS.2020.2972339
6. A study of the impact of spatial resolution on the estimation of particle matter concentration from the aerosol optical depth retrieved from satellite observations L. Mei et al. https://doi.org/10.1080/01431161.2019.1601279
7. SEVIRI Aerosol Optical Depth Validation Using AERONET and Intercomparison with MODIS in Central and Eastern Europe N. Ajtai et al. https://doi.org/10.3390/rs13050844
8. On the retrieval of aerosol optical depth over cryosphere using passive remote sensing L. Mei et al. https://doi.org/10.1016/j.rse.2020.111731
9. A Critical Evaluation of Deep Blue Algorithm Derived AVHRR Aerosol Product Over China L. Mei et al. https://doi.org/10.1029/2018JD029929
10. Estimating ground-level particulate matter concentrations using satellite-based data: a review M. Shin et al. https://doi.org/10.1080/15481603.2019.1703288
11. Understanding MODIS dark-target collection 5 and 6 aerosol data over China: Effect of surface type, aerosol loading and aerosol absorption L. Mei et al. https://doi.org/10.1016/j.atmosres.2019.05.023
12. A fast and accurate radiative transfer model for aerosol remote sensing L. Mei et al. https://doi.org/10.1016/j.jqsrt.2020.107270
13. Time series retrieval of Multi-wavelength Aerosol optical depth by adapting Transformer (TMAT) using Himawari-8 AHI data L. She et al. https://doi.org/10.1016/j.rse.2024.114115
14. Extending XBAER Algorithm to Aerosol and Cloud Condition L. Mei et al. https://doi.org/10.1109/TGRS.2019.2919910
15. Possible influence of sudden stratospheric warmings on the atmospheric environment in the Beijing–Tianjin–Hebei region Q. Lu et al. https://doi.org/10.5194/acp-22-13087-2022
16. Application of XBAER aerosol optical depth retrieval algorithm to hyperspectral EnMAP satellite data S. Laffoy et al. https://doi.org/10.5194/amt-19-293-2026
17. Validation of Aerosol Products from AATSR and MERIS/AATSR Synergy Algorithms—Part 1: Global Evaluation Y. Che et al. https://doi.org/10.3390/rs10091414
18. Tempo-spatial patterns of PM2.5 measured using a portable particulate monitor around a mine complex in Canada’s Arctic W. Chen et al. https://doi.org/10.1007/s10661-021-09376-5
19. An Improved Aerosol Optical Depth Retrieval Algorithm for Multiangle Directional Polarimetric Camera (DPC) B. Ge et al. https://doi.org/10.3390/rs14164045
20. Atmospheric aerosol measurements from the ATSR-SLSTR series of dual-view satellite instruments 1995–2022 K. Pearson et al. https://doi.org/10.1038/s41597-025-04694-6
21. The retrieval of ice cloud parameters from multi-spectral satellite observations of reflectance using a modified XBAER algorithm L. Mei et al. https://doi.org/10.1016/j.rse.2018.06.007
22. A generalized land surface reflectance reconstruction method for aerosol retrieval: Application to the Particulate Observing Scanning Polarimeter (POSP) onboard GaoFen-5 (02) satellite Z. Shi et al. https://doi.org/10.1016/j.rse.2023.113683
23. AeroTrans: Hourly AOD retrieval over land from MSG-1/SEVIRI imagery integrating Transformer and transfer learning Y. Fan et al. https://doi.org/10.1016/j.rse.2026.115268