37 citations as recorded by crossref.

1. 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
2. Comparison and evaluation of MODIS Multi-angle Implementation of Atmospheric Correction (MAIAC) aerosol product over South Asia A. Mhawish et al. 10.1016/j.rse.2019.01.033
3. Satellite-based estimation of the impacts of summertime wildfires on PM<sub>2.5</sub> concentration in the United States Z. Xue et al. 10.5194/acp-21-11243-2021
4. MAIAC Thermal Technique for Smoke Injection Height From MODIS A. Lyapustin et al. 10.1109/LGRS.2019.2936332
5. MODIS high-resolution MAIAC aerosol product: Global validation and analysis W. Qin et al. 10.1016/j.atmosenv.2021.118684
6. Observations of the Interaction and Transport of Fine Mode Aerosols With Cloud and/or Fog in Northeast Asia From Aerosol Robotic Network and Satellite Remote Sensing T. Eck et al. 10.1029/2018JD028313
7. 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
8. Aerosol optical depth assimilation for a size-resolved sectional model: impacts of observationally constrained, multi-wavelength and fine mode retrievals on regional scale analyses and forecasts P. Saide et al. 10.5194/acp-13-10425-2013
9. The impact of different aerosol layering conditions on the high-resolution MODIS/MAIAC AOD retrieval bias: The uncertainty analysis I. Rogozovsky et al. 10.1016/j.atmosenv.2023.119930
10. Satellite-based aerosol optical depth estimates over the continental U.S. during the 2020 wildfire season: Roles of smoke and land cover J. Daniels et al. 10.1016/j.scitotenv.2024.171122
11. Assessment of urban aerosol pollution over the Moscow megacity by the MAIAC aerosol product E. Zhdanova et al. 10.5194/amt-13-877-2020
12. Assessment of air pollution in Krasnoyarsk based on satellite data of different spatial resolution K. Krasnoshchekov & O. Yakubailik 10.1088/1757-899X/537/6/062083
13. Observed aerosol-induced radiative effect on plant productivity in the eastern United States S. Strada et al. 10.1016/j.atmosenv.2015.09.051
14. A Cloud masking algorithm for the XBAER aerosol retrieval using MERIS data L. Mei et al. 10.1016/j.rse.2016.11.016
15. The Relationship Between MAIAC Smoke Plume Heights and Surface PM M. Cheeseman et al. 10.1029/2020GL088949
16. Wildfire Smoke Cools Summer River and Stream Water Temperatures A. David et al. 10.1029/2018WR022964
17. Ensemble-based deep learning for estimating PM2.5 over California with multisource big data including wildfire smoke L. Li et al. 10.1016/j.envint.2020.106143
18. Satellite Observations of Cloud-Related Variations in Aerosol Properties T. Várnai & A. Marshak 10.3390/atmos9110430
19. Connecting Crop Productivity, Residue Fires, and Air Quality over Northern India H. Jethva et al. 10.1038/s41598-019-52799-x
20. Fine particulate matter predictions using high resolution Aerosol Optical Depth (AOD) retrievals A. Chudnovsky et al. 10.1016/j.atmosenv.2014.02.019
21. Accuracy assessment of MODIS land aerosol optical thickness algorithms using AERONET measurements over North America H. Jethva et al. 10.5194/amt-12-4291-2019
22. Satellite remote sensing of aerosol optical depth: advances, challenges, and perspectives X. Wei et al. 10.1080/10643389.2019.1665944
23. Satellite‐Based Daily PM2.5 Estimates During Fire Seasons in Colorado G. Geng et al. 10.1029/2018JD028573
24. A Novel Atmospheric Correction Algorithm to Exploit the Diurnal Variability in Hypertemporal Geostationary Observations W. Wang et al. 10.3390/rs14040964
25. MODIS-based smoke detection shows that daily smoke cover dampens fire severity in initial burns but not reburns in complex terrain L. Harris & A. Taylor 10.1071/WF22061
26. A novel ensemble-based statistical approach to estimate daily wildfire-specific PM2.5 in California (2006–2020) R. Aguilera et al. 10.1016/j.envint.2022.107719
27. Characterization of forest fire smoke event near Washington, DC in summer 2013 with multi-wavelength lidar I. Veselovskii et al. 10.5194/acp-15-1647-2015
28. MODIS Collection 6 MAIAC algorithm A. Lyapustin et al. 10.5194/amt-11-5741-2018
29. Assessment of Atmospheric Correction Methods for Sentinel-2 MSI Images Applied to Amazon Floodplain Lakes V. Martins et al. 10.3390/rs9040322
30. Features of the Extreme Fire Season of 2021 in Yakutia (Eastern Siberia) and Heavy Air Pollution Caused by Biomass Burning O. Tomshin & V. Solovyev 10.3390/rs14194980
31. A critical assessment of high-resolution aerosol optical depth retrievals for fine particulate matter predictions A. Chudnovsky et al. 10.5194/acp-13-10907-2013
32. A Novel Ensemble-Based Statistical Approach to Estimate Daily Wildfire-Specific Pm2.5 in California (2006-2020) R. Aguilera et al. 10.2139/ssrn.4177030
33. Development and Evaluation of a North America Ensemble Wildfire Air Quality Forecast: Initial Application to the 2020 Western United States “Gigafire” P. Makkaroon et al. 10.1029/2022JD037298
34. Forest Fire Smoke Detection Research Based on the Random Forest Algorithm and Sub-Pixel Mapping Method X. Li et al. 10.3390/f14030485
35. Spatiotemporal variations and long term trends analysis of aerosol optical depth over the United Arab Emirates A. Abuelgasim et al. 10.1016/j.rsase.2021.100532
36. First Provisional Land Surface Reflectance Product from Geostationary Satellite Himawari-8 AHI S. Li et al. 10.3390/rs11242990
37. Estimating ground-level PM2.5 concentrations in the Southeastern United States using MAIAC AOD retrievals and a two-stage model X. Hu et al. 10.1016/j.rse.2013.08.032