65 citations as recorded by crossref.

1. Intercomparison of Multiple Satellite Aerosol Products against AERONET over the North China Plain X. Fan et al. 10.3390/atmos10090480
2. The Collection 6 MODIS aerosol products over land and ocean R. Levy et al. 10.5194/amt-6-2989-2013
3. Studying the Impact on Urban Health over the Greater Delta Region in Egypt Due to Aerosol Variability Using Optical Characteristics from Satellite Observations and Ground-Based AERONET Measurements W. Li et al. 10.3390/rs11171998
4. Development and assessment of a higher-spatial-resolution (4.4 km) MISR aerosol optical depth product using AERONET-DRAGON data M. Garay et al. 10.5194/acp-17-5095-2017
5. Impact of Aerosol and Cloud on the Solar Energy Potential over the Central Gangetic Himalayan Region U. Dumka et al. 10.3390/rs13163248
6. Dust impact on surface solar irradiance assessed with model simulations, satellite observations and ground-based measurements P. Kosmopoulos et al. 10.5194/amt-10-2435-2017
7. Observational Constraints on the Aerosol Optical Depth–Surface PM2.5 Relationship during Alaskan Wildfire Seasons T. Zhao et al. 10.1021/acsestair.4c00120
8. Diurnal time representation of MODIS, VIIRS, MISR, and AHI over Asia and Oceania Z. Yang et al. 10.1016/j.rse.2023.113878
9. Long-term validation of MODIS C6 and C6.1 Dark Target aerosol products over China using CARSNET and AERONET H. Che et al. 10.1016/j.chemosphere.2019.06.238
10. Model-enforced post-process correction of satellite aerosol retrievals A. Lipponen et al. 10.5194/amt-14-2981-2021
11. Differences between the MODIS Collection 6 and 5.1 aerosol datasets over the greater Mediterranean region A. Georgoulias et al. 10.1016/j.atmosenv.2016.10.014
12. Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain J. Zhu et al. 10.3390/rs9050432
13. Deep-learning-based post-process correction of the aerosol parameters in the high-resolution Sentinel-3 Level-2 Synergy product A. Lipponen et al. 10.5194/amt-15-895-2022
14. Global evaluation of NOAA-20 VIIRS dark target aerosol products over land and ocean X. Pei et al. 10.1016/j.atmosenv.2024.120949
15. Spatio-temporal variability of Suomi-NPP VIIRS-derived aerosol optical thickness over China in 2013 F. Meng et al. 10.1016/j.rse.2015.03.005
16. Global validation and comparison of MODIS DT and POLDER-3 GRASP aerosol products over ocean X. Pei et al. 10.1016/j.atmosres.2022.106480
17. Improved MODIS Dark Target aerosol optical depth algorithm over land: angular effect correction Y. Wu et al. 10.5194/amt-9-5575-2016
18. Accuracy assessment of Terra-MODIS aerosol optical depth retrievals S. Safarpour et al. 10.1088/1755-1315/20/1/012059
19. Exploring Aerosols Near Clouds With High‐Spatial‐Resolution Aircraft Remote Sensing During SEAC4RS R. Spencer et al. 10.1029/2018JD028989
20. Comparison of Aerosol Optical Depth from MODIS Product Collection 6.1 and AERONET in the Western United States I. Eibedingil et al. 10.3390/rs13122316
21. Precipitable water vapor over oceans from the Maritime Aerosol Network: Evaluation of global models and satellite products under clear sky conditions D. Pérez-Ramírez et al. 10.1016/j.atmosres.2018.09.007
22. 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
23. Evaluation of Aqua MODIS Collection 6 AOD Parameters for Air Quality Research over the Continental United States J. Belle & Y. Liu 10.3390/rs8100815
24. Evaluation of the multi‐angle implementation of atmospheric correction (MAIAC) aerosol algorithm through intercomparison with VIIRS aerosol products and AERONET S. Superczynski et al. 10.1002/2016JD025720
25. The effect of South American biomass burning aerosol emissions on the regional climate G. Thornhill et al. 10.5194/acp-18-5321-2018
26. Simulation of the spatial distribution of mineral dust and its direct radiative forcing over Australia O. Choobari et al. 10.3402/tellusb.v65i0.19856
27. Long-term statistical assessment of Aqua-MODIS aerosol optical depth over coastal regions: bias characteristics and uncertainty sources J. Anderson et al. 10.3402/tellusb.v65i0.20805
28. Impact of the Dust Aerosol Model on the VIIRS Aerosol Optical Depth (AOD) Product across China Y. Wang et al. 10.3390/rs12060991
29. Can MODIS detect trends in aerosol optical depth over land? X. Fan et al. 10.1007/s00376-017-7017-2
30. Improved Aerosol Optical Depth and Ångstrom Exponent Retrieval Over Land From MODIS Based on the Non-Lambertian Forward Model . Leiku Yang et al. 10.1109/LGRS.2014.2303317
31. Validation of MODIS-Aqua Aerosol Products C051 and C006 over the Beijing-Tianjin-Hebei Region K. Wang et al. 10.3390/atmos8090172
32. Assessing the Challenges of Surface‐Level Aerosol Mass Estimates From Remote Sensing During the SEAC4RS and SEARCH Campaigns: Baseline Surface Observations and Remote Sensing in the Southeastern United States K. Kaku et al. 10.1029/2017JD028074
33. Investigating the Aerosol Optical Depth and Angstrom Exponent and Their Relationships with Meteorological Parameters Over Lahore in Pakistan S. Tariq & Z. ul-Haq 10.1007/s40010-018-0575-6
34. Performance of MODIS C6 Aerosol Product during Frequent Haze-Fog Events: A Case Study of Beijing W. Chen et al. 10.3390/rs9050496
35. Exploring systematic offsets between aerosol products from the two MODIS sensors R. Levy et al. 10.5194/amt-11-4073-2018
36. Validation of MODIS 3 km land aerosol optical depth from NASA's EOS Terra and Aqua missions P. Gupta et al. 10.5194/amt-11-3145-2018
37. Evaluation and comparison of MODIS and MISR aerosol products with ground-based monitoring stations in the Amazon Basin V. Schumacher et al. 10.1016/j.atmosenv.2024.120597
38. The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future L. Remer et al. 10.3390/rs12182900
39. Semi-supervised combination of experts for aerosol optical depth estimation N. Djuric et al. 10.1016/j.artint.2015.09.010
40. Google Earth Engine–assisted black carbon radiative forcing calculation over a heavy industrial city in China W. Chen et al. 10.1007/s11869-020-00796-9
41. Collocation mismatch uncertainties in satellite aerosol retrieval validation T. Virtanen et al. 10.5194/amt-11-925-2018
42. Validation and expected error estimation of Suomi‐NPP VIIRS aerosol optical thickness and Ångström exponent with AERONET J. Huang et al. 10.1002/2016JD024834
43. Big data analyses for determining the spatio-temporal trends of air pollution due to wildfires in California using Google Earth Engine A. Saim & M. Aly 10.1016/j.apr.2024.102226
44. Graph-regularized low-rank representation for aerosol optical depth retrieval Y. Sun et al. 10.1080/01431161.2016.1249302
45. Graph Regularized Nonlinear Ridge Regression for Remote Sensing Data Analysis R. Hang et al. 10.1109/JSTARS.2016.2574802
46. An Evaluation of MODIS-Retrieved Aerosol Optical Depth over AERONET Sites in Alaska A. McPhetres & S. Aggarwal 10.3390/rs10091384
47. Intercomparison and assessment of long-term (2004–2013) multiple satellite aerosol products over two contrasting sites in South Africa A. Adesina et al. 10.1016/j.jastp.2016.09.001
48. Validation of MODIS Aerosol Optical Depth Retrieval over Mountains in Central China Based on a Sun-Sky Radiometer Site of SONET Y. Ma et al. 10.3390/rs8020111
49. A Modified Aerosol Free Vegetation Index Algorithm for Aerosol Optical Depth Retrieval Using GOSAT TANSO-CAI Data G. Zhong et al. 10.3390/rs8120998
50. 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
51. Reconstructing aerosol optical depth using spatiotemporal Long Short-Term Memory convolutional autoencoder L. Liang et al. 10.1038/s41597-023-02696-w
52. Coherent uncertainty analysis of aerosol measurements from multiple satellite sensors M. Petrenko & C. Ichoku 10.5194/acp-13-6777-2013
53. Impact of environmental pollution on the retrieval of hourly aerosol products from Advanced Himawari Imager (AHI) over Beijing Q. Xu et al. 10.1016/j.apr.2020.03.007
54. A New Cloud and Haze Mask Algorithm From Radiative Transfer Simulations Coupled With Machine Learning Y. Jiao et al. 10.1109/TGRS.2023.3252264
55. Applying the Dark Target Aerosol Algorithm to MERSI-II: Retrieval and Validation of Aerosol Optical Depth over the Ocean X. Pei et al. 10.1007/s00376-024-4032-y
56. Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network M. Kim et al. 10.3390/rs15143621
57. Long-term trends in air quality in major cities in the UK and India: a view from space K. Vohra et al. 10.5194/acp-21-6275-2021
58. Bayesian aerosol retrieval algorithm for MODIS AOD retrieval over land A. Lipponen et al. 10.5194/amt-11-1529-2018
59. Applying the Dark Target aerosol algorithm with Advanced Himawari Imager observations during the KORUS-AQ field campaign P. Gupta et al. 10.5194/amt-12-6557-2019
60. Aerosol radiative forcing efficiency in the UV-B region over central Argentina G. Palancar et al. 10.1016/j.atmosres.2016.02.016
61. Correcting MODIS aerosol optical depth products using a ridge regression model R. Hang et al. 10.1080/01431161.2018.1439597
62. Introducing the 4.4 km spatial resolution Multi-Angle Imaging SpectroRadiometer (MISR) aerosol product M. Garay et al. 10.5194/amt-13-593-2020
63. Gaussian Conditional Random Fields for Aggregation of Operational Aerosol Retrievals N. Djuric et al. 10.1109/LGRS.2014.2361154
64. Tracking Smoke from a Prescribed Fire and Its Impacts on Local Air Quality Using Temporally Resolved GOES-16 ABI Aerosol Optical Depth (AOD) A. Huff et al. 10.1175/JTECH-D-20-0162.1
65. MODIS 3 km aerosol product: algorithm and global perspective L. Remer et al. 10.5194/amt-6-1829-2013