42 citations as recorded by crossref.

1. Validation of MODIS Aerosol Products with AERONET Measurements of Different Land Cover Types in Areas over Eastern Europe and China M. Filonchyk & V. Hurynovich 10.1007/s41651-020-00052-9
2. Examining the policy-practice gap- The issue of crop burning induced Particulate Matter pollution in Northwest India L. Kaushal 10.1080/20964129.2020.1846460
3. Assessment of Satellite AOD during the 2020 Wildfire Season in the Western U.S. X. Ye et al. 10.3390/rs14236113
4. The (mis)identification of high-latitude dust events using remote sensing methods in the Yukon, Canada: a sub-daily variability analysis R. Huck et al. 10.5194/acp-23-6299-2023
5. Aerosol Optical Thickness Retrieval in Presence of Cloud: Application to S3A/SLSTR Observations M. Luffarelli et al. 10.3390/atmos13050691
6. Improvement of aerosol optical depth data for localized solar resource assessment C. Lin et al. 10.1016/j.solener.2022.11.047
7. Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring C. Chen et al. 10.5194/essd-12-3573-2020
8. An Estimation Method for PM2.5 Based on Aerosol Optical Depth Obtained from Remote Sensing Image Processing and Meteorological Factors J. Gu et al. 10.3390/rs14071617
9. Estimating ground-level PM2.5 using micro-satellite images by a convolutional neural network and random forest approach T. Zheng et al. 10.1016/j.atmosenv.2020.117451
10. Impact of environmental attributes on the uncertainty in MAIAC/MODIS AOD retrievals: A comparative analysis S. Falah et al. 10.1016/j.atmosenv.2021.118659
11. Validation and Analysis of MAIAC AOD Aerosol Products in East Asia from 2011 to 2020 P. Wang et al. 10.3390/rs14225735
12. Aerosol Optical Depth Retrieval for Sentinel-2 Based on Convolutional Neural Network Method J. Jiang et al. 10.3390/atmos14091400
13. Advances in the estimation of high Spatio-temporal resolution pan-African top-down biomass burning emissions made using geostationary fire radiative power (FRP) and MAIAC aerosol optical depth (AOD) data H. Nguyen & M. Wooster 10.1016/j.rse.2020.111971
14. Smoke‐Driven Changes in Photosynthetically Active Radiation During the U.S. Agricultural Growing Season K. Corwin et al. 10.1029/2022JD037446
15. Aerosol optical depth over Northeastern Brazil: A multi-platform intercomparison study G. Münchow et al. 10.1016/j.atmosres.2024.107864
16. Evaluation and Comparison of MODIS C6 and C6.1 Deep Blue Aerosol Products in Arid and Semi-Arid Areas of Northwestern China L. Yang et al. 10.3390/rs14081935
17. Spatio-temporal air quality assessment in Tehran, Iran, during the COVID-19 lockdown periods M. Bagherinia et al. 10.1080/10106049.2023.2169374
18. An Evaluation of Two Decades of Aerosol Optical Depth Retrievals from MODIS over Australia M. Shaylor et al. 10.3390/rs14112664
19. Retrievals of Aerosol Optical Depth and Spectral Absorption From DSCOVR EPIC A. Lyapustin et al. 10.3389/frsen.2021.645794
20. Estimation of High-Resolution PM2.5 over the Indo-Gangetic Plain by Fusion of Satellite Data, Meteorology, and Land Use Variables A. Mhawish et al. 10.1021/acs.est.0c01769
21. Assessment of urban aerosol pollution over the Moscow megacity by the MAIAC aerosol product E. Zhdanova et al. 10.5194/amt-13-877-2020
22. Evaluation and intercomparison of wildfire smoke forecasts from multiple modeling systems for the 2019 Williams Flats fire X. Ye et al. 10.5194/acp-21-14427-2021
23. Evaluation and comparison of MODIS and VIIRS aerosol optical depth (AOD) products over regions in the Eastern Mediterranean and the Black Sea P. Ettehadi Osgouei et al. 10.1016/j.atmosenv.2021.118784
24. Retrieval uncertainty and consistency of Suomi-NPP VIIRS Deep Blue and Dark Target aerosol products under diverse aerosol loading scenarios over South Asia K. Aditi et al. 10.1016/j.envpol.2023.121913
25. Research progress, challenges, and prospects of PM2.5 concentration estimation using satellite data S. Zhu et al. 10.1139/er-2022-0125
26. A Comparison of Multi-Angle Implementation of Atmospheric Correction and MOD09 Daily Surface Reflectance Products From MODIS A. Lyapustin et al. 10.3389/frsen.2021.712093
27. The influence and contribution of fine mode particles to aerosol optical properties during haze events at the foothills of Himalaya-Karakorum region S. Mohyuddin et al. 10.1016/j.atmosenv.2022.119388
28. Advances in solar forecasting: Computer vision with deep learning Q. Paletta et al. 10.1016/j.adapen.2023.100150
29. An intercomparison of SEMARA high-resolution AOD and MODIS operational AODs M. Bagherinia et al. 10.1016/j.apr.2023.102023
30. AEROCOM and AEROSAT AAOD and SSA study – Part 1: Evaluation and intercomparison of satellite measurements N. Schutgens et al. 10.5194/acp-21-6895-2021
31. Spatial analysis of particulate matter (PM10) using MODIS aerosol optical thickness observations and GIS over East Malaysia A. Najim et al. 10.1016/j.ejrs.2023.03.001
32. Variation of Aerosol Optical Properties over Cluj-Napoca, Romania, Based on 10 Years of AERONET Data and MODIS MAIAC AOD Product H. Ștefănie et al. 10.3390/rs15123072
33. Evaluation of atmospheric effects on the performance of neural network and regression tree in FCOVER modelling A. Shamsoddini & A. Zeydani 10.61186/jgst.14.2.89
34. Potential of AOD Retrieval Using Atmospheric Emitted Radiance Interferometer (AERI) J. Seo et al. 10.3390/rs14020407
35. Global evaluation of Fengyun-3 MERSI dark target aerosol retrievals over land L. Yang et al. 10.1080/17538947.2024.2344580
36. Monitoring and simulation of a 7-day dust episode and associated dust radiative forcing over the Middle East via synergy of satellite observations, reanalysis datasets and regional/numerical models K. Mohammadpour et al. 10.1016/j.atmosres.2025.107948
37. Retrieval of total and fine mode aerosol optical depth by an improved MODIS Dark Target algorithm X. Su et al. 10.1016/j.envint.2022.107343
38. Dust in the Critical Zone: North American case studies J. Brahney et al. 10.1016/j.earscirev.2024.104942
39. An Overview of the Applications of Earth Observation Satellite Data: Impacts and Future Trends Q. Zhao et al. 10.3390/rs14081863
40. Spatially lagged predictors from a wider area improve PM2.5 estimation at a finer temporal interval—A case study of Dallas-Fort Worth, United States Y. Karale & M. Yuan 10.3389/frsen.2023.1041466
41. Long-term validation and error analysis of DB and MAIAC aerosol products over bright surface of China W. Ji et al. 10.1016/j.atmosres.2023.107106
42. MODIS Collection 6 MAIAC algorithm A. Lyapustin et al. 10.5194/amt-11-5741-2018