118 citations as recorded by crossref.

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2. Modeling Parametric Forecasts of Solar Energy over Time in the Mid-North Area of Mozambique F. Mucomole et al. https://doi.org/10.3390/en18061469
3. Extended aerosol and surface characterization from S5P/TROPOMI with GRASP algorithm. Part II: Global validation and Intercomparison C. Chen et al. https://doi.org/10.1016/j.rse.2024.114374
4. Has China been exporting less particulate air pollution over the past decade? J. Zhang et al. https://doi.org/10.1002/2017GL072617
5. Evaluation and comparison of CMIP6 models and MERRA-2 reanalysis AOD against Satellite observations from 2000 to 2014 over China M. Ali et al. https://doi.org/10.1016/j.gsf.2021.101325
6. Correcting for trace gas absorption when retrieving aerosol optical depth from satellite observations of reflected shortwave radiation F. Patadia et al. https://doi.org/10.5194/amt-11-3205-2018
7. Quantitative inversion of integrated hyperspectral and optical remote sensing images to monitor dust distribution in open pit mines S. Feng & J. Zhang https://doi.org/10.1080/27669645.2025.2468101
8. Impact of Optical Aerosol Depth (AOD) on Light Pollution Level: a spatio-temporal analysis A. Ayudyanti & I. Hidayati https://doi.org/10.1088/1755-1315/884/1/012037
9. Discerning the pre-monsoon urban atmosphere aerosol characteristic and its potential source type remotely sensed by AERONET over the Bengal Gangetic plain B. Priyadharshini et al. https://doi.org/10.1007/s11356-018-2290-x
10. Validation of MODIS 3 km land aerosol optical depth from NASA's EOS Terra and Aqua missions P. Gupta et al. https://doi.org/10.5194/amt-11-3145-2018
11. Satellite observed trends of global mean net atmospheric shortwave and longwave irradiances and diabatic heating by precipitation S. Kato et al. https://doi.org/10.1126/sciadv.adz1292
12. MAIAC-based climatology of atmospheric iron-oxide dust species from DSCOVR EPIC observations S. Go et al. https://doi.org/10.3389/frsen.2025.1676851
13. Spatiotemporal characteristics of aerosols and their trends over mainland China with the recent Collection 6 MODIS and OMI satellite datasets K. Hu et al. https://doi.org/10.1007/s11356-017-0715-6
14. Retrieving Aerosol Characteristics From the PACE Mission, Part 1: Ocean Color Instrument L. Remer et al. https://doi.org/10.3389/feart.2019.00152
15. Assessment of the aerosol optical depths measured by satellite-based passive remote sensors in the Alberta oil sands region C. Sioris et al. https://doi.org/10.5194/acp-17-1931-2017
16. Variability of Major Aerosol Types in China Classified Using AERONET Measurements L. Zhang & J. Li https://doi.org/10.3390/rs11202334
17. A Comprehensive Machine and Deep Learning Approach for Aerosol Optical Depth Forecasting: New Evidence from the Arabian Peninsula A. Alban et al. https://doi.org/10.1007/s41748-024-00398-w
18. A critical view of long-term AVHRR aerosol data record in China: Retrieval frequency and heavy pollution M. Tao et al. https://doi.org/10.1016/j.atmosenv.2019.117246
19. Empirical Correlation Weighting (ECW) Spatial Interpolation Method for Satellite Aerosol Optical Depth Products by MODIS AOD over Northern China in 2016 Y. Wang et al. https://doi.org/10.3390/rs15184462
20. 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
21. A Review on Estimation of Particulate Matter from Satellite-Based Aerosol Optical Depth: Data, Methods, and Challenges A. Ranjan et al. https://doi.org/10.1007/s13143-020-00215-0
22. Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager M. Kim et al. https://doi.org/10.5194/amt-17-1913-2024
23. Impact of environmental pollution on the retrieval of AOD products from Visible Infrared Imaging Radiometer Suite (VIIRS) over wuhan Y. Ma et al. https://doi.org/10.1016/j.apr.2019.09.014
24. Superior PM2.5 Estimation by Integrating Aerosol Fine Mode Data from the Himawari-8 Satellite in Deep and Classical Machine Learning Models Z. Zang et al. https://doi.org/10.3390/rs13142779
25. Interannual variability and trends of combustion aerosol and dust in major continental outflows revealed by MODIS retrievals and CAM5 simulations during 2003–2017 H. Yu et al. https://doi.org/10.5194/acp-20-139-2020
26. Estimates of the aerosol indirect effect over the Baltic Sea region derived from 12 years of MODIS observations G. Saponaro et al. https://doi.org/10.5194/acp-17-3133-2017
27. Initial constraints on triggering mechanisms of the eruption of Fuego volcano (Guatemala) from 3 June 2018 using IASI satellite data F. Pardini et al. https://doi.org/10.1016/j.jvolgeores.2019.03.014
28. Historical (1850–2014) Aerosol Evolution and Role on Climate Forcing Using the GISS ModelE2.1 Contribution to CMIP6 S. Bauer et al. https://doi.org/10.1029/2019MS001978
29. Estimating daily PM2.5 concentrations using an extreme gradient boosting model based on VIIRS aerosol products over southeastern Europe S. Gündoğdu et al. https://doi.org/10.1007/s11869-022-01245-5
30. Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors A. van Donkelaar et al. https://doi.org/10.1021/acs.est.5b05833
31. Optical Modeling of Single Asian Dust and Marine Air Particles: A Comparison with Geometric Particle Shapes for Remote Sensing J. Conny et al. https://doi.org/10.1016/j.jqsrt.2020.107197
32. Retrieval of aerosol optical properties from GOCI-II observations: Continuation of long-term geostationary aerosol monitoring over East Asia S. Lee et al. https://doi.org/10.1016/j.scitotenv.2023.166504
33. Parametric Forecast of Solar Energy over Time by Applying Machine Learning Techniques: Systematic Review F. Mucomole et al. https://doi.org/10.3390/en18061460
34. Continental-scale surface reflectance product from CBERS-4 MUX data: Assessment of atmospheric correction method using coincident Landsat observations V. Martins et al. https://doi.org/10.1016/j.rse.2018.09.017
35. Impact of the choice of the satellite aerosol optical depth product in a sub-regional dust emission inversion J. Escribano et al. https://doi.org/10.5194/acp-17-7111-2017
36. Annual and Inter-annual Variability Coupled with Comparison of MODIS-AERONET Retrieved Aerosol Optical Depth over a Rural Site in the Central Indo-Gangetic Basin S. Varpe et al. https://doi.org/10.1007/s41810-022-00135-8
37. Leveraging JEDI for atmospheric composition: a unified framework for evaluating observations and model forecasts S. Wei et al. https://doi.org/10.5194/gmd-19-8367-2026
38. An Improved Method for Retrieving Aerosol Optical Depth Using Gaofen-1 WFV Camera Data F. Yang et al. https://doi.org/10.3390/rs13020280
39. Towards long-term, high-accuracy, and continuous satellite total and fine-mode aerosol records: Enhanced Land General Aerosol (e-LaGA) retrieval algorithm for VIIRS L. Wang et al. https://doi.org/10.1016/j.isprsjprs.2024.06.022
40. New estimates of aerosol radiative effects over India from surface and satellite observations T. Subba et al. https://doi.org/10.1016/j.atmosres.2022.106254
41. Worldwide validation of CAMS and MERRA-2 reanalysis aerosol optical depth products using 15 years of AERONET observations C. Gueymard & D. Yang https://doi.org/10.1016/j.atmosenv.2019.117216
42. Spatiotemporal Investigations of Aerosol Optical Properties Over Bangladesh for the Period 2002–2016 M. Islam et al. https://doi.org/10.1007/s41748-019-00120-1
43. Validation and Comparison of Long-Term Accuracy and Stability of Global Reanalysis and Satellite Retrieval AOD X. Su et al. https://doi.org/10.3390/rs16173304
44. Investigation on spatiotemporal distribution of aerosol optical properties over two oceanic regions surrounding Indian subcontinent during summer monsoon season C. Vachaspati et al. https://doi.org/10.1007/s11356-018-2682-y
45. A Dark Target Algorithm for the GOSAT TANSO-CAI Sensor in Aerosol Optical Depth Retrieval over Land G. Zhong et al. https://doi.org/10.3390/rs9060524
46. The AERONET Version 3 aerosol retrieval algorithm, associated uncertainties and comparisons to Version 2 A. Sinyuk et al. https://doi.org/10.5194/amt-13-3375-2020
47. Composite Aerosol Optical Depth Mapping over Northeast Asia from GEO-LEO Satellite Observations S. Ahn et al. https://doi.org/10.3390/rs13061096
48. Large contribution of meteorological factors to inter-decadal changes in regional aerosol optical depth H. Che et al. https://doi.org/10.5194/acp-19-10497-2019
49. Temporal variation of surface reflectance and cloud fraction used to identify background aerosol retrieval information over East Asia S. Park et al. https://doi.org/10.1016/j.atmosenv.2023.119916
50. Aerosol Optical Depth Retrieval Over Ocean and Land From Fengyun-3F MERSI-III: First Results and Validation L. Yang et al. https://doi.org/10.1109/JSTARS.2025.3613696
51. Satellite remote sensing of aerosol optical depth: advances, challenges, and perspectives X. Wei et al. https://doi.org/10.1080/10643389.2019.1665944
52. Analysis of AOD from MODIS-Merged DT–DB Products Over the Arabian Peninsula M. Ali & M. Assiri https://doi.org/10.1007/s41748-019-00108-x
53. Spatial and Temporal Variations of Aerosol Optical Thickness over the China Seas from Himawari-8 Q. Tu et al. https://doi.org/10.3390/rs13245082
54. Experimental Parametric Forecast of Solar Energy over Time: Sample Data Descriptor F. Mucomole et al. https://doi.org/10.3390/data10030037
55. Improving AOD Algorithm Evaluation: A Spatial Matching Method for Minimizing Quality Control Bias B. Du et al. https://doi.org/10.3390/rs17071235
56. Weekday AOD smaller than weekend AOD in eastern China on the basis of the MODIS AOD product J. Song et al. https://doi.org/10.1007/s00704-017-2142-5
57. Differences between the MODIS Collection 6 and 5.1 aerosol datasets over the greater Mediterranean region A. Georgoulias et al. https://doi.org/10.1016/j.atmosenv.2016.10.014
58. Regional sulfate drives long-term rise in AOD over megacity Kolkata, India P. Rawat et al. https://doi.org/10.1016/j.atmosenv.2019.04.031
59. Evaluation of the Consistency of Several XAERDT Aerosol Products Over Land and Ocean X. Pei et al. https://doi.org/10.1109/TGRS.2026.3694737
60. Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba J. Antuña-Marrero et al. https://doi.org/10.5194/amt-11-2279-2018
61. Validation of high‐resolution MAIAC aerosol product over South America V. Martins et al. https://doi.org/10.1002/2016JD026301
62. Diurnal time representation of MODIS, VIIRS, MISR, and AHI over Asia and Oceania Z. Yang et al. https://doi.org/10.1016/j.rse.2023.113878
63. High Spatial Resolution PM2.5 Retrieval Using MODIS and Ground Observation Station Data Based on Ensemble Random Forest X. Chen et al. https://doi.org/10.1109/ACCESS.2019.2908975
64. Space‐Borne Estimation of Volcanic Sulfate Aerosol Lifetime C. Li & R. Cohen https://doi.org/10.1029/2020JD033883
65. Multi-step evaluation framework for analyzing mineral dust transport and meteorological impacts over northern India S. Budakoti https://doi.org/10.1016/j.jaridenv.2025.105389
66. Performance evaluation of MODIS and VIIRS satellite AOD products over the Indian subcontinent S. Payra et al. https://doi.org/10.3389/fenvs.2023.1158641
67. A New Cloud and Haze Mask Algorithm From Radiative Transfer Simulations Coupled With Machine Learning Y. Jiao et al. https://doi.org/10.1109/TGRS.2023.3252264
68. Comprehensive Validation and Comparison of Three VIIRS Aerosol Products over the Ocean on a Global Scale W. Li et al. https://doi.org/10.3390/rs14112544
69. Optimized retrievals of aerosol optical properties from directional polarimetric camera using optimal linear mixture of basis aerosol models supported by the non-negative matrix factorization S. Jin et al. https://doi.org/10.1016/j.rse.2026.115504
70. Tropospheric SO2 and NO2 in 2012–2018: Contrasting views of two sensors (OMI and OMPS) from space Y. Wang & J. Wang https://doi.org/10.1016/j.atmosenv.2019.117214
71. Spatial-Temporal Distribution and Microphysical Characteristics of Aerosols and Clouds over China: A Combined Satellite and Aircraft Observation Study Y. Che et al. https://doi.org/10.3390/rs18162796
72. Radiative interaction of atmosphere and surface: Write-up with elements of code S. Korkin & A. Lyapustin https://doi.org/10.1016/j.jqsrt.2023.108663
73. Potential of AOD Retrieval Using Atmospheric Emitted Radiance Interferometer (AERI) J. Seo et al. https://doi.org/10.3390/rs14020407
74. Aerosol radiative forcing of forest fires unprecedented in South Korea (2022) captured by Korean geostationary satellites, GK-2A AMI and GK-2B GEMS D. Seong et al. https://doi.org/10.1016/j.envpol.2024.123464
75. Preliminary Investigation of a New AHI Aerosol Optical Depth (AOD) Retrieval Algorithm and Evaluation with Multiple Source AOD Measurements in China F. Yang et al. https://doi.org/10.3390/rs10050748
76. Employing relaxed smoothness constraints on imaginary part of refractive index in AERONET aerosol retrieval algorithm A. Sinyuk et al. https://doi.org/10.5194/amt-15-4135-2022
77. Evaluation of MODIS columnar aerosol retrievals using AERONET in semi-arid Nevada and California, U.S.A., during the summer of 2012 S. Loría-Salazar et al. https://doi.org/10.1016/j.atmosenv.2016.08.070
78. Effect of Lockdown on Pollutant Levels in the Delhi Megacity: Role of Local Emission Sources and Chemical Lifetimes C. Mallik et al. https://doi.org/10.3389/fenvs.2021.743894
79. Temporal evolution of aerosols and their extreme events in polluted Asian regions during Terra's 20-year observations Z. Hu et al. https://doi.org/10.1016/j.rse.2021.112541
80. Assessing FY-3D MERSI-II Observations for Vegetation Dynamics Monitoring: A Performance Test of Land Surface Reflectance K. Yang et al. https://doi.org/10.1109/TGRS.2023.3348997
81. Long-term validation and error analysis of MODIS and VIIRS dark target aerosol products in Africa X. Xue et al. https://doi.org/10.1016/j.atmosres.2025.108372
82. Development, Production and Evaluation of Aerosol Climate Data Records from European Satellite Observations (Aerosol_cci) T. Popp et al. https://doi.org/10.3390/rs8050421
83. Estudo da Variabilidade Temporal da Profundidade Óptica do Aerossol Utilizando Dados de Sensoriamento Remoto Sobre a Região de Transição entre a Floresta Amazônica e o Cerrado N. Prado & S. da Costa Coelho https://doi.org/10.1590/0102-7786324012
84. JEDI‐Based Three‐Dimensional Ensemble‐Variational Data Assimilation System for Global Aerosol Forecasting at NCEP B. Huang et al. https://doi.org/10.1029/2022MS003232
85. Circular polarization in atmospheric aerosols S. Gassó & K. Knobelspiesse https://doi.org/10.5194/acp-22-13581-2022
86. Integration of Surface Reflectance and Aerosol Retrieval Algorithms for Multi-Resolution Aerosol Optical Depth Retrievals over Urban Areas M. Bilal et al. https://doi.org/10.3390/rs14020373
87. Investigations of MODIS AOD and cloud properties with CERES sensor based net cloud radiative effect and a NOAA HYSPLIT Model over Bangladesh for the period 2001–2016 M. Ali et al. https://doi.org/10.1016/j.atmosres.2018.09.001
88. AEROsol generic classification using a novel Satellite remote sensing Approach (AEROSA) M. Bilal et al. https://doi.org/10.3389/fenvs.2022.981522
89. Aerosol Information Retrieval from GF-5B DPC Data over North China Using the Dark Dense Vegetation Algorithm R. Zhang et al. https://doi.org/10.3390/atmos14020241
90. Global evaluation of Fengyun-3 MERSI dark target aerosol retrievals over land L. Yang et al. https://doi.org/10.1080/17538947.2024.2344580
91. Applying the Dark Target aerosol algorithm with Advanced Himawari Imager observations during the KORUS-AQ field campaign P. Gupta et al. https://doi.org/10.5194/amt-12-6557-2019
92. Continuing the MODIS Dark Target Aerosol Time Series with VIIRS V. Sawyer et al. https://doi.org/10.3390/rs12020308
93. Exploring Aerosols Near Clouds With High‐Spatial‐Resolution Aircraft Remote Sensing During SEAC4RS R. Spencer et al. https://doi.org/10.1029/2018JD028989
94. A Critical Evaluation of Deep Blue Algorithm Derived AVHRR Aerosol Product Over China L. Mei et al. https://doi.org/10.1029/2018JD029929
95. Effect of Shape and Sizes of Crystal Particles on Angular Distributions of Transmitted Solar Radiation in Two Sensing Geometries: Results of Numerical Simulation T. Zhuravleva https://doi.org/10.1134/S1024856021010127
96. Applying the Dark Target Aerosol Algorithm to MERSI-II: Retrieval and Validation of Aerosol Optical Depth over the Ocean X. Pei et al. https://doi.org/10.1007/s00376-024-4032-y
97. The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future L. Remer et al. https://doi.org/10.3390/rs12182900
98. Assessment of Satellite AOD during the 2020 Wildfire Season in the Western U.S. X. Ye et al. https://doi.org/10.3390/rs14236113
99. Satellite Hyperspectral Nighttime Light Observation and Identification with DESIS R. Ryan et al. https://doi.org/10.3390/rs16050923
100. Validation of SOAR VIIRS Over‐Water Aerosol Retrievals and Context Within the Global Satellite Aerosol Data Record A. Sayer et al. https://doi.org/10.1029/2018JD029465
101. Aerosol Retrieval Method Using Multi-Angle Data from GF-5 02 DPC over the Jing–Jin–Ji Region Z. Wang et al. https://doi.org/10.3390/rs17081415
102. Impact of the Dust Aerosol Model on the VIIRS Aerosol Optical Depth (AOD) Product across China Y. Wang et al. https://doi.org/10.3390/rs12060991
103. Global evaluation of NOAA-20 VIIRS dark target aerosol products over land and ocean X. Pei et al. https://doi.org/10.1016/j.atmosenv.2024.120949
104. 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
105. Cross-calibration of S-NPP VIIRS moderate-resolution reflective solar bands against MODIS Aqua over dark water scenes A. Sayer et al. https://doi.org/10.5194/amt-10-1425-2017
106. Satellite derived air pollution climatology over India and its neighboring regions: Spatio-temporal trends and insights S. Dhankar et al. https://doi.org/10.1016/j.pce.2024.103769
107. Towards a satellite formaldehyde – in situ hybrid estimate for organic aerosol abundance J. Liao et al. https://doi.org/10.5194/acp-19-2765-2019
108. Observational Constraints on the Aerosol Optical Depth–Surface PM2.5 Relationship during Alaskan Wildfire Seasons T. Zhao et al. https://doi.org/10.1021/acsestair.4c00120
109. First retrieval of daily 160 m aerosol optical depth over urban areas using Gaofen-1/6 synergistic observations: Algorithm development and validation J. Dong et al. https://doi.org/10.1016/j.isprsjprs.2024.04.020
110. 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. https://doi.org/10.1029/2022JD037298
111. Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain J. Zhu et al. https://doi.org/10.3390/rs9050432
112. Secular Changes in Atmospheric Turbidity over Iraq and a Possible Link to Military Activity A. Chudnovsky & A. Kostinski https://doi.org/10.3390/rs12091526
113. Long-term distribution and evolution trends of absorption aerosol optical depth with different chemical components in global and typical regions H. Zhao et al. https://doi.org/10.1016/j.atmosres.2024.107819
114. Estimating PM2.5 surface concentrations from AOD: A combination of SLSTR and MODIS J. Handschuh et al. https://doi.org/10.1016/j.rsase.2022.100716
115. 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. https://doi.org/10.1029/2018JD028313
116. 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. https://doi.org/10.3390/rs11171998
117. The Earth‐Observing Aqua Satellite Mission: 20 Years and Counting C. Parkinson https://doi.org/10.1029/2022EA002481
118. Multisensor Data Synergy of Terra-MODIS, Aqua-MODIS, and Suomi NPP-VIIRS for the Retrieval of Aerosol Optical Depth and Land Surface Reflectance Properties S. Shi et al. https://doi.org/10.1109/TGRS.2018.2835508