120 citations as recorded by crossref.

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3. MODIS 3 km aerosol product: algorithm and global perspective L. Remer et al. 10.5194/amt-6-1829-2013
4. Evaluation of MODIS Collection 6 aerosol retrieval algorithms over Indo-Gangetic Plain: Implications of aerosols types and mass loading A. Mhawish et al. 10.1016/j.rse.2017.09.016
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7. Estimation of ground-level dry PM2.5 concentrations at 3 km resolution over Beijing using Geostationary Ocean Colour Imager J. Wang & Z. Li 10.1080/2150704X.2020.1795298
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9. 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. 10.1080/01431161.2019.1601279
10. Estimating PM2.5 surface concentrations from AOD: A combination of SLSTR and MODIS J. Handschuh et al. 10.1016/j.rsase.2022.100716
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12. Seasonal monitoring and estimation of regional aerosol distribution over Po valley, northern Italy, using a high-resolution MAIAC product B. Arvani et al. 10.1016/j.atmosenv.2016.06.037
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18. Evaluation of the MODIS Collection 6.1 3 km aerosol optical depth product over China M. Zhang et al. 10.1016/j.atmosenv.2022.118970
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23. Analysis of Primary Air Pollutants’ Spatiotemporal Distributions Based on Satellite Imagery and Machine-Learning Techniques Y. Li et al. 10.3390/atmos15030287
24. 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
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28. Validation, comparison, and integration of GOCI, AHI, MODIS, MISR, and VIIRS aerosol optical depth over East Asia during the 2016 KORUS-AQ campaign M. Choi et al. 10.5194/amt-12-4619-2019
29. Interaction between urban heat island and urban pollution island during summer in Berlin H. Li et al. 10.1016/j.scitotenv.2018.04.254
30. Evaluation of MODIS aerosol retrieval algorithms over the Beijing‐Tianjin‐Hebei region during low to very high pollution events M. Bilal & J. Nichol 10.1002/2015JD023082
31. Systematic Evaluation of Four Satellite AOD Datasets for Estimating PM2.5 Using a Random Forest Approach J. Handschuh et al. 10.3390/rs15082064
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34. Validation and Accuracy Analysis of Global MODIS Aerosol Products over Land Q. Wang et al. 10.3390/atmos8080155
35. Assessment of urban aerosol pollution over the Moscow megacity by the MAIAC aerosol product E. Zhdanova et al. 10.5194/amt-13-877-2020
36. MODIS Collection 6.1 3 km resolution aerosol optical depth product: global evaluation and uncertainty analysis J. Wei et al. 10.1016/j.atmosenv.2020.117768
37. Aerosol Optical Depth Retrieval over Bright Areas Using Landsat 8 OLI Images L. Sun et al. 10.3390/rs8010023
38. Long Temporal Analysis of 3-km MODIS Aerosol Product Over East China Q. Ma et al. 10.1109/JSTARS.2017.2650144
39. Satellite-based PM2.5 estimation using fine-mode aerosol optical thickness over China X. Yan et al. 10.1016/j.atmosenv.2017.09.023
40. Estimating Regional Ground‐Level PM2.5 Directly From Satellite Top‐Of‐Atmosphere Reflectance Using Deep Belief Networks H. Shen et al. 10.1029/2018JD028759
41. Variation of the aerosol optical properties and validation of MODIS AOD products over the eastern edge of the Tibetan Plateau based on ground-based remote sensing in 2017 Y. You et al. 10.1016/j.atmosenv.2019.117257
42. Multi-Spectrum Hierarchical Segmentation Algorithm: A New Aerosol Optical Thickness Retrieval Algorithm for Urban Areas Y. Chen et al. 10.1109/LGRS.2021.3117282
43. 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
44. An improved algorithm for retrieving the fine-mode fraction of aerosol optical thickness, part 1: Algorithm development X. Yan et al. 10.1016/j.rse.2017.02.005
45. Extreme Aerosol Events Over Eastern North America: 1. Characterizing and Simulating Historical Events Y. Guo et al. 10.1029/2020JD033758
46. The Influence of Underlying Land Cover on the Accuracy of MODIS C6.1 Aerosol Products—A Case Study over the Yangtze River Delta Region of China K. Sun et al. 10.3390/rs14040938
47. Evaluation of MODIS Dark Target AOD Product with 3 and 10 km Resolution in Amazonia R. Palácios et al. 10.3390/atmos13111742
48. Daily estimation of ground-level PM2.5 concentrations at 4 km resolution over Beijing-Tianjin-Hebei by fusing MODIS AOD and ground observations B. Lv et al. 10.1016/j.scitotenv.2016.12.049
49. Development of non-linear models predicting daily fine particle concentrations using aerosol optical depth retrievals and ground-based measurements at a municipality in the Brazilian Amazon region K. Gonçalves et al. 10.1016/j.atmosenv.2018.03.057
50. Potential Approach for Single-Peak Extinction Fitting of Aerosol Profiles Based on In Situ Measurements for the Improvement of Surface PM2.5 Retrieval from Satellite AOD Product T. Lin et al. 10.3390/rs12132174
51. Performance of MODIS aerosol products at various timescales and in different pollution conditions over eastern Asia Q. Mao et al. 10.1007/s11431-018-9462-5
52. Point-surface fusion of station measurements and satellite observations for mapping PM2.5 distribution in China: Methods and assessment T. Li et al. 10.1016/j.atmosenv.2017.01.004
53. Estimating Particulate Matter using satellite based aerosol optical depth and meteorological variables in Malaysia N. Kamarul Zaman et al. 10.1016/j.atmosres.2017.04.019
54. First TanSat CO2 retrieval over land and ocean using both nadir and glint spectroscopy X. Hong et al. 10.1016/j.rse.2024.114053
55. Evaluation of Aerosol Optical Depth (AOD) and PM2.5 associations for air quality assessment Z. Yang et al. 10.1016/j.rsase.2020.100396
56. Monitoring the Impacts of Wildfires on Forest Ecosystems and Public Health in the Exo-Urban Environment Using High-Resolution Satellite Aerosol Products from the Visible Infrared Imaging Radiometer Suite (VIIRS) A. Huff et al. 10.4137/EHI.S19590
57. 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
58. GIST-PM-Asia v1: development of a numerical system to improve particulate matter forecasts in South Korea using geostationary satellite-retrieved aerosol optical data over Northeast Asia S. Lee et al. 10.5194/gmd-9-17-2016
59. Validation of MODIS C6 Dark Target Aerosol Products at 3 km and 10 km Spatial Resolutions Over the China Seas and the Eastern Indian Ocean X. Shen et al. 10.3390/rs10040573
60. Estimating ground-level PM2.5 over a coastal region of China using satellite AOD and a combined model L. Yang et al. 10.1016/j.jclepro.2019.04.231
61. A New MODIS C6 Dark Target and Deep Blue Merged Aerosol Product on a 3 km Spatial Grid M. Bilal et al. 10.3390/rs10030463
62. A Novel Atmospheric Correction Algorithm to Exploit the Diurnal Variability in Hypertemporal Geostationary Observations W. Wang et al. 10.3390/rs14040964
63. Investigation of air quality over the largest city in central China using high resolution satellite derived aerosol optical depth data K. Sun et al. 10.1016/j.apr.2017.12.011
64. Prediction of PM2.5 concentration based on the CEEMDAN-RLMD-BiLSTM-LEC model Q. Guo et al. 10.7717/peerj.15931
65. Simplified and Fast Atmospheric Radiative Transfer model for satellite-based aerosol optical depth retrieval X. Yan et al. 10.1016/j.atmosenv.2020.117362
66. Effect of MODIS Terra radiometric calibration improvements on Collection 6 Deep Blue aerosol products: Validation and Terra/Aqua consistency A. Sayer et al. 10.1002/2015JD023878
67. An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks B. Holben et al. 10.5194/acp-18-655-2018
68. Size-resolved particulate matter concentrations derived from 4.4 km-resolution size-fractionated Multi-angle Imaging SpectroRadiometer (MISR) aerosol optical depth over Southern California M. Franklin et al. 10.1016/j.rse.2017.05.002
69. A surface reflectance scheme for retrieving aerosol optical depth over urban surfaces in MODIS Dark Target retrieval algorithm P. Gupta et al. 10.5194/amt-9-3293-2016
70. Implications of MODIS bow-tie distortion on aerosol optical depth retrievals, and techniques for mitigation A. Sayer et al. 10.5194/amt-8-5277-2015
71. Daily Estimation of Ground-Level PM2.5 Concentrations over Beijing Using 3 km Resolution MODIS AOD Y. Xie et al. 10.1021/acs.est.5b01413
72. A new method of satellite-based haze aerosol monitoring over the North China Plain and a comparison with MODIS Collection 6 aerosol products X. Yan et al. 10.1016/j.atmosres.2015.12.003
73. High Resolution Aerosol Optical Depth Retrieval Using Gaofen-1 WFV Camera Data K. Sun et al. 10.3390/rs9010089
74. High-resolution estimation of PM2.5 concentrations across China using multiple machine learning approaches and model fusion L. Meng et al. 10.1016/j.apr.2024.102110
75. Development of a remote sensing algorithm to retrieve atmospheric aerosol properties using multiwavelength and multipixel information M. Hashimoto & T. Nakajima 10.1002/2016JD025698
76. Aerosol Optical Depth Retrieval From Landsat 8 OLI Images Over Urban Areas Supported by MODIS BRDF/Albedo Data X. Tian et al. 10.1109/LGRS.2018.2827200
77. An Evaluation of Four MODIS Collection 6 Aerosol Products in a Humid Subtropical Region M. Zhang et al. 10.3390/rs9111173
78. A minimum albedo aerosol retrieval method for the new-generation geostationary meteorological satellite Himawari-8 X. Yan et al. 10.1016/j.atmosres.2018.02.021
79. 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
80. Machine learning driven by environmental covariates to estimate high-resolution PM2.5 in data-poor regions X. Jin et al. 10.7717/peerj.13203
81. Estimating ground-level PM2.5 concentrations in Beijing using a satellite-based geographically and temporally weighted regression model Y. Guo et al. 10.1016/j.rse.2017.06.001
82. Evaluating MODIS and MISR aerosol optical depth retrievals over environmentally distinct sites in Pakistan G. Ali et al. 10.1016/j.jastp.2018.12.008
83. 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
84. Integration of Surface Reflectance and Aerosol Retrieval Algorithms for Multi-Resolution Aerosol Optical Depth Retrievals over Urban Areas M. Bilal et al. 10.3390/rs14020373
85. SAHARA: A Simplified AtmospHeric Correction AlgoRithm for Chinese gAofen Data: 1. Aerosol Algorithm L. She et al. 10.3390/rs9030253
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87. Validation of MODIS 3 km Resolution Aerosol Optical Depth Retrievals Over Asia J. Nichol & M. Bilal 10.3390/rs8040328
88. 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
89. Retrieving High-Resolution Aerosol Optical Depth from GF-4 PMS Imagery in Eastern China Z. Sun et al. 10.3390/rs13183752
90. 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
91. PM2.5 over North China based on MODIS AOD and effect of meteorological elements during 2003–2015 Y. Chen et al. 10.1007/s11783-019-1202-8
92. Evaluation of satellite-based aerosol datasets and the CAMS reanalysis over the ocean utilizing shipborne reference observations J. Witthuhn et al. 10.5194/amt-13-1387-2020
93. Interpretation of satellite retrievals of PM2.5 over the southern African Interior M. Kneen et al. 10.1016/j.atmosenv.2015.12.016
94. Validation of MODIS and VIIRS derived aerosol optical depth over complex coastal waters M. Bilal et al. 10.1016/j.atmosres.2016.11.009
95. National-Scale Estimates of Ground-Level PM2.5 Concentration in China Using Geographically Weighted Regression Based on 3 km Resolution MODIS AOD W. You et al. 10.3390/rs8030184
96. Evaluating the potential for application of MODIS satellite data for urban air quality monitoring in Vietnam B. Hieu et al. 10.1088/1757-899X/869/2/022035
97. Overview of atmospheric aerosol studies in Malaysia: Known and unknown K. Kanniah et al. 10.1016/j.atmosres.2016.08.002
98. Prediction of PM2.5 in an Urban Area of Northern Thailand Using Multivariate Linear Regression Model T. Amnuaylojaroen & I. Levy 10.1155/2022/3190484
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109. Evaluation of Aqua MODIS Collection 6 AOD Parameters for Air Quality Research over the Continental United States J. Belle & Y. Liu 10.3390/rs8100815
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112. Exploring Aerosols Near Clouds With High‐Spatial‐Resolution Aircraft Remote Sensing During SEAC4RS R. Spencer et al. 10.1029/2018JD028989
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118. 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
119. Validation and Accuracy Analysis of the Collection 6.1 MODIS Aerosol Optical Depth Over the Westernmost City in China Based on the Sun‐Sky Radiometer Observations From SONET G. Huang et al. 10.1029/2019EA001041
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