143 citations as recorded by crossref.

1. Study on Spatial Changes in PM2.5 before and after the COVID-19 Pandemic in Southwest China X. Li et al. 10.3390/atmos14040671
2. National Civil Space Infrastructure Satellite Aerosol Product Validation Network (SIAVNET) measurements: Supporting satellite aerosol product validation for different surface types over China T. Cheng et al. 10.1016/j.atmosres.2022.106508
3. Spatio-temporal changes of AOD in Xinjiang of China from 2000 to 2019: Which factor is more influential, natural factor or human factor? J. Li et al. 10.1371/journal.pone.0253942
4. Long-time series aerosol optical depth retrieval from AVHRR data over land in North China and Central Europe Y. Xue et al. 10.1016/j.rse.2017.06.036
5. 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
6. Investigating the Spatial and Temporal Limitations for Remote Sensing of Wildfire Smoke Using Satellite and Airborne Imagers During FIREX‐AQ Y. Shi et al. 10.1029/2023JD039085
7. Retrieval of 500 m Aerosol Optical Depths from MODIS Measurements over Urban Surfaces under Heavy Aerosol Loading Conditions in Winter S. Jin et al. 10.3390/rs11192218
8. 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. 10.3390/rs15184462
9. Fusing Retrievals of High Resolution Aerosol Optical Depth from Landsat-8 and Sentinel-2 Observations over Urban Areas H. Lin et al. 10.3390/rs13204140
10. Spatial characteristics and temporal evolution of the relationship between PM2.5 and aerosol optical depth over the eastern USA during 2003–2017 Q. Jin et al. 10.1016/j.atmosenv.2020.117718
11. MODIS Collection 6.1 aerosol optical depth products over land and ocean: validation and comparison J. Wei et al. 10.1016/j.atmosenv.2018.12.004
12. 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
13. 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
14. Relative contributions of component-segregated aerosols to trends in aerosol optical depth over land (2007–2019): Insights from CAMS aerosol reanalysis H. Zhao et al. 10.1016/j.atmosenv.2024.120676
15. Substantial Underestimation of Fine-Mode Aerosol Loading from Wildfires and Its Radiative Effects in Current Satellite-Based Retrievals over the United States X. Yan et al. 10.1021/acs.est.4c02498
16. Factor analysis for aerosol optical depth and its prediction from the perspective of land-use change W. Zhang et al. 10.1016/j.ecolind.2018.05.026
17. Characteristics of Remotely Sensed Urban Pollution Island (UPI) & its Linkage with Surface Urban Heat Island (SUHI) over Eastern India A. Barat & P. Parth Sarthi 10.1007/s41810-023-00176-7
18. The health impacts of Indonesian peatland fires L. Hein et al. 10.1186/s12940-022-00872-w
19. A Simple Band Ratio Library (BRL) Algorithm for Retrieval of Hourly Aerosol Optical Depth Using FY-4A AGRI Geostationary Satellite Data X. Jiang et al. 10.3390/rs14194861
20. Performance of MODIS Collection 6.1 Level 3 aerosol products in spatial-temporal variations over land J. Wei et al. 10.1016/j.atmosenv.2019.03.001
21. 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
22. Review of retrieval of aerosol optical depth to estimate particle concentration and its challenges based on spatiotemporal relationships by various spectroradiometer models C. Samuel et al. 10.1002/gj.4780
23. A comprehensive reappraisal of long-term aerosol characteristics, trends, and variability in Asia S. Jin et al. 10.5194/acp-23-8187-2023
24. Improving the Estimation of PM2.5 Concentration in the North China Area by Introducing an Attention Mechanism into Random Forest L. Zhang et al. 10.3390/atmos15030384
25. A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing A. Sayer et al. 10.5194/amt-13-373-2020
26. Assessment of the impact of discontinuity in satellite instruments and retrievals on global PM2.5 estimates M. Hammer et al. 10.1016/j.rse.2023.113624
27. Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements Y. Tong et al. 10.3390/rs12142330
28. Assesment of Coronavirus Pandemic Effect on Air Quality in Cyprus S. ÇAKIR & M. PRİNCEWİLL 10.31590/ejosat.1038697
29. Integration of GOCI and AHI Yonsei aerosol optical depth products during the 2016 KORUS-AQ and 2018 EMeRGe campaigns H. Lim et al. 10.5194/amt-14-4575-2021
30. Continuing the MODIS Dark Target Aerosol Time Series with VIIRS V. Sawyer et al. 10.3390/rs12020308
31. Retrieving aerosols single scattering albedo from MODIS reflectances Q. Wang et al. 10.1016/j.atmosres.2022.106381
32. An Improved Aerosol Retrieval Algorithm Based on Nonlinear Surface Model From FY-3D/MERSI-II Remote Sensing Data Y. Si et al. 10.1109/TGRS.2024.3367883
33. Retrieval of high-resolution aerosol optical depth (AOD) using Landsat 8 imageries over different LULC classes over a city along Indo-Gangetic Plain, India R. Singh et al. 10.1007/s10661-024-12631-0
34. The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future L. Remer et al. 10.3390/rs12182900
35. 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
36. Global evaluation of Fengyun-3 MERSI dark target aerosol retrievals over land L. Yang et al. 10.1080/17538947.2024.2344580
37. Instant and delayed effects of March biomass burning aerosols over the Indochina Peninsula A. Zhu et al. 10.5194/acp-22-15425-2022
38. Direct aerosol optical depth retrievals using MODIS reflectance data and machine learning over East Asia E. Kang et al. 10.1016/j.atmosenv.2023.119951
39. Himawari-8/AHI and MODIS Aerosol Optical Depths in China: Evaluation and Comparison T. Jiang et al. 10.3390/rs11091011
40. Validation and inter-comparison of MODIS and VIIRS aerosol optical depth products against data from multiple observation networks over East China Y. Su et al. 10.1016/j.atmosenv.2021.118205
41. Comparison and evaluation of the simulated annual aerosol characteristics over China with two global aerosol models Y. Cheng et al. 10.1016/j.scitotenv.2020.143003
42. Surface and satellite observations of air pollution in India during COVID-19 lockdown: Implication to air quality Y. Sathe et al. 10.1016/j.scs.2020.102688
43. Estimation of pan-European, daily total, fine-mode and coarse-mode Aerosol Optical Depth at 0.1° resolution to facilitate air quality assessments Z. Chen et al. 10.1016/j.scitotenv.2024.170593
44. Investigating multiple aerosol optical depth products from MODIS and VIIRS over Asia: Evaluation, comparison, and merging Y. Wang et al. 10.1016/j.atmosenv.2020.117548
45. Retrieval of hourly PM2.5 using top-of-atmosphere reflectance from geostationary ocean color imagers I and II H. Choi et al. 10.1016/j.envpol.2023.121169
46. A review of statistical methods used for developing large-scale and long-term PM2.5 models from satellite data Z. Ma et al. 10.1016/j.rse.2021.112827
47. 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. 10.3390/rs10050748
48. Evaluation of Terra-MODIS C6 and C6.1 Aerosol Products against Beijing, XiangHe, and Xinglong AERONET Sites in China during 2004-2014 M. Bilal et al. 10.3390/rs11050486
49. AERONET Remotely Sensed Measurements and Retrievals of Biomass Burning Aerosol Optical Properties During the 2015 Indonesian Burning Season T. Eck et al. 10.1029/2018JD030182
50. The atmospheric aerosol spatial distribution and tropical intra-seasonal oscillations over the South Asian region B. Sanatan et al. 10.1016/j.apr.2024.102199
51. Performance of MODIS C6.1 Dark Target and Deep Blue aerosol products in Delhi National Capital Region, India: Application for aerosol studies V. Sharma et al. 10.1016/j.apr.2021.01.023
52. A Review on Estimation of Particulate Matter from Satellite-Based Aerosol Optical Depth: Data, Methods, and Challenges A. Ranjan et al. 10.1007/s13143-020-00215-0
53. 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
54. Aerosol Retrieval Algorithm for Sentinel-2 Images Over Complex Urban Areas Y. Yang et al. 10.1109/TGRS.2022.3158061
55. Long-Range Transport of Aerosols and Regional Sources Using MODIS and NASA MERRA Reanalysis Over South Asia B. Sanatan et al. 10.1007/s41748-024-00478-x
56. Gap-filling MODIS daily aerosol optical depth products by developing a spatiotemporal fitting algorithm T. Zhang et al. 10.1080/15481603.2022.2060596
57. Evaluating VIIRS EPS Aerosol Optical Depth in China: An intercomparison against ground-based measurements and MODIS C. Li et al. 10.1016/j.jqsrt.2018.12.002
58. Refining aerosol optical depth retrievals over land by constructing the relationship of spectral surface reflectances through deep learning: Application to Himawari-8 T. Su et al. 10.1016/j.rse.2020.112093
59. Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager M. Kim et al. 10.5194/amt-17-1913-2024
60. Large-scale MODIS AOD products recovery: Spatial-temporal hybrid fusion considering aerosol variation mitigation Y. Wang et al. 10.1016/j.isprsjprs.2019.08.017
61. AHI/Himawari-8 Yonsei Aerosol Retrieval (YAER): Algorithm, Validation and Merged Products H. Lim et al. 10.3390/rs10050699
62. Evaluation and comparison of multiangle implementation of the atmospheric correction algorithm, Dark Target, and Deep Blue aerosol products over China N. Liu et al. 10.5194/acp-19-8243-2019
63. Long-term spatiotemporal distribution characterization of atmospheric black carbon MERRA-2 concentration over China Q. Mao et al. 10.1016/j.apr.2024.102295
64. Validation, inter-comparison, and usage recommendation of six latest VIIRS and MODIS aerosol products over the ocean and land on the global and regional scales X. Su et al. 10.1016/j.scitotenv.2023.163794
65. Evaluation of the AVHRR DeepBlue aerosol optical depth dataset over mainland China Y. Che et al. 10.1016/j.isprsjprs.2018.09.004
66. Mitigating MODIS AOD non-random sampling error on surface PM2.5 estimates by a combined use of Bayesian Maximum Entropy method and linear mixed-effects model D. Fu et al. 10.1016/j.apr.2019.11.020
67. Exploring Aerosols Near Clouds With High‐Spatial‐Resolution Aircraft Remote Sensing During SEAC4RS R. Spencer et al. 10.1029/2018JD028989
68. GOCI Yonsei aerosol retrieval version 2 products: an improved algorithm and error analysis with uncertainty estimation from 5-year validation over East Asia M. Choi et al. 10.5194/amt-11-385-2018
69. 20 years of columnar aerosol properties at Valencia area (Eastern Spain) by ground-based sun-photometry M. Garcia-Suñer et al. 10.1016/j.atmosres.2023.107198
70. Synergistic Use of Hyperspectral UV-Visible OMI and Broadband Meteorological Imager MODIS Data for a Merged Aerosol Product S. Go et al. 10.3390/rs12233987
71. 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
72. 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
73. Comparison and evaluation of multiple satellite aerosol products over China in different scenarios under a unified criterion: Preparation for consistent and high-quality dataset construction H. Zhu et al. 10.1016/j.atmosres.2022.106374
74. An Adaptive Dark-Target Algorithm for Retrieving Land AOD Applied to FY-4B/AGRI Data Y. Si et al. 10.1109/JSTARS.2024.3408251
75. Exploring systematic offsets between aerosol products from the two MODIS sensors R. Levy et al. 10.5194/amt-11-4073-2018
76. Characterizing the 2015 Indonesia fire event using modified MODIS aerosol retrievals Y. Shi et al. 10.5194/acp-19-259-2019
77. High-resolution aerosol retrieval over urban areas using sentinel-2 data Y. Yang et al. 10.1016/j.atmosres.2021.105829
78. Estimation of AOD Under Uncertainty: An Approach for Hyperspectral Airborne Data N. Bhatia et al. 10.3390/rs10060947
79. Difference between global and regional aerosol model classifications and associated implications for spaceborne aerosol optical depth retrieval P. Zhou et al. 10.1016/j.atmosenv.2023.119674
80. A Spatio-Temporal Weighted Filling Method for Missing AOD Values R. Gao et al. 10.3390/atmos13071080
81. How Long Is Too Long? Variogram Analysis of AERONET Data to Aid Aerosol Validation and Intercomparison Studies A. Sayer 10.1029/2020EA001290
82. Validation and Accuracy Assessment of MODIS C6.1 Aerosol Products over the Heavy Aerosol Loading Area X. Tian & Z. Gao 10.3390/atmos10090548
83. Improved retrievals of aerosol optical depth and fine mode fraction from GOCI geostationary satellite data using machine learning over East Asia Y. Kang et al. 10.1016/j.isprsjprs.2021.11.016
84. How Does COVID-19 Lockdown Impact Air Quality in India? Z. Hu et al. 10.3390/rs14081869
85. Unveiling the Transparency of Prediction Models for Spatial PM2.5 over Singapore: Comparison of Different Machine Learning Approaches with eXplainable Artificial Intelligence M. Sunder et al. 10.3390/ai4040040
86. Columnar optical characteristics and radiative properties of aerosols of the AERONET site in Minsk, Belarus M. Filonchyk et al. 10.1016/j.atmosenv.2021.118237
87. Quantifying PM2.5 mass concentration and particle radius using satellite data and an optical-mass conversion algorithm M. Liu et al. 10.1016/j.isprsjprs.2019.10.010
88. Evaluation of MODIS DT, DB, and MAIAC Aerosol Products over Different Land Cover Types in the Yangtze River Delta of China J. Jiang et al. 10.3390/rs15010275
89. Global evaluation of NOAA-20 VIIRS dark target aerosol products over land and ocean X. Pei et al. 10.1016/j.atmosenv.2024.120949
90. Global Validation of MODIS C6 and C6.1 Merged Aerosol Products over Diverse Vegetated Surfaces M. Bilal et al. 10.3390/rs10030475
91. 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
92. An Investigation on Shenzhen Urban Green Space Changes and Their Effect on Local Eco-Environment in Recent Decades Y. Liu et al. 10.3390/su132212549
93. Aerosol optical depth climatology from the high-resolution MAIAC product over Europe: differences between major European cities and their surrounding environments L. Di Antonio et al. 10.5194/acp-23-12455-2023
94. Geographical coverage analysis and usage suggestions of temporal averaged aerosol optical depth product from GOES-R satellite data X. Jiang et al. 10.1080/01431161.2024.2331978
95. Comparison of MODIS- and CALIPSO-Derived Temporal Aerosol Optical Depth over Yellow River Basin (China) from 2007 to 2015 Z. Zhang et al. 10.1007/s41748-020-00181-7
96. Satellite-based PM2.5 estimation directly from reflectance at the top of the atmosphere using a machine learning algorithm J. Liu et al. 10.1016/j.atmosenv.2019.04.002
97. Influence of industrial sustainability transition on air quality in a typical resource-exhausted city J. Wang & X. Li 10.1016/j.heliyon.2024.e25138
98. Bayesian aerosol retrieval algorithm for MODIS AOD retrieval over land A. Lipponen et al. 10.5194/amt-11-1529-2018
99. Performance of MODIS high-resolution MAIAC aerosol algorithm in China: Characterization and limitation M. Tao et al. 10.1016/j.atmosenv.2019.06.004
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103. Estimation of ground-level particulate matter concentrations based on synergistic use of MODIS, MERRA-2 and AERONET AODs over a coastal site in the Eastern Mediterranean G. Tuna Tuygun et al. 10.1016/j.atmosenv.2021.118562
104. Spatiotemporal Variations of Aerosols in China during the COVID-19 Pandemic Lockdown J. Yao et al. 10.3390/rs14030696
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106. Google Earth Engine based spatio-temporal analysis of air pollutants before and during the first wave COVID-19 outbreak over Turkey via remote sensing F. Ghasempour et al. 10.1016/j.jclepro.2021.128599
107. 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
108. Evaluation and Comparison of MODIS Collection 6.1 and Collection 6 Dark Target Aerosol Optical Depth over Mainland China Under Various Conditions Including Spatiotemporal Distribution, Haze Effects, and Underlying Surface Y. Huang et al. 10.1029/2019EA000809
109. Global Estimates and Long-Term Trends of Fine Particulate Matter Concentrations (1998–2018) M. Hammer et al. 10.1021/acs.est.0c01764
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112. Improvement of snow/haze confusion data gaps in MODIS Dark Target aerosol retrievals in East China X. Zhang et al. 10.1016/j.atmosres.2020.105063
113. The polarization crossfire (PCF) sensor suite focusing on satellite remote sensing of fine particulate matter PM2.5 from space Z. Li et al. 10.1016/j.jqsrt.2022.108217
114. Reconstructing aerosol optical depth using spatiotemporal Long Short-Term Memory convolutional autoencoder L. Liang et al. 10.1038/s41597-023-02696-w
115. Understanding MODIS dark-target collection 5 and 6 aerosol data over China: Effect of surface type, aerosol loading and aerosol absorption L. Mei et al. 10.1016/j.atmosres.2019.05.023
116. 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
117. 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
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119. Intercomparison in spatial distributions and temporal trends derived from multi-source satellite aerosol products J. Wei et al. 10.5194/acp-19-7183-2019
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121. 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
122. MODIS AOD sampling rate and its effect on PM2.5 estimation in North China Z. Song et al. 10.1016/j.atmosenv.2019.04.020
123. 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
124. Multi-angle aerosol optical depth retrieval method based on improved surface reflectance L. Chen et al. 10.5194/amt-17-4411-2024
125. Evaluation of MODIS, MISR, and VIIRS daily level-3 aerosol optical depth products over land Q. Chen et al. 10.1016/j.atmosres.2021.105810
126. Improved merge schemes for MODIS Collection 6.1 Dark Target and Deep Blue combined aerosol products J. Wei et al. 10.1016/j.atmosenv.2019.01.016
127. Increasing aerosol optical depth spatial and temporal availability by merging datasets from geostationary and sun-synchronous satellites P. Gupta et al. 10.5194/amt-17-5455-2024
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129. Aerosol optical depth (AOD): spatial and temporal variations and association with meteorological covariates in Taklimakan desert, China J. Li et al. 10.7717/peerj.10542
130. Investigating the spatio-temporal correlation between urban heat island and atmospheric pollution island interaction over Delhi, India using geospatial techniques M. Mishra & A. Mathew 10.1007/s12517-022-10854-4
131. A Dark Target Algorithm for the GOSAT TANSO-CAI Sensor in Aerosol Optical Depth Retrieval over Land G. Zhong et al. 10.3390/rs9060524
132. A comprehensive review delineates advancements in retrieving particulate matter utilising satellite aerosol optical depth: Parameter consideration, data processing, models development and future perspectives S. Padimala & C. Matli 10.1016/j.atmosres.2024.107514
133. Merging regional and global aerosol optical depth records from major available satellite products L. Sogacheva et al. 10.5194/acp-20-2031-2020
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135. An improved deep learning network for AOD retrieving from remote sensing imagery focusing on sub-pixel cloud H. Cai et al. 10.1080/15481603.2023.2262836
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137. VIIRS Environmental Data Record and Deep Blue aerosol products: validation, comparison, and spatiotemporal variations from 2013 to 2018 in China L. He et al. 10.1016/j.atmosenv.2021.118265
138. Local region partition for person re-identification H. Chu et al. 10.1007/s11042-017-4817-4
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140. Aerosol data assimilation in the MOCAGE chemical transport model during the TRAQA/ChArMEx campaign: lidar observations L. El Amraoui et al. 10.5194/amt-13-4645-2020
141. Fusion of Multisource Satellite AOD Products via Bayesian Maximum Entropy With Explicit A Priori Knowledge H. Zhu et al. 10.1109/TGRS.2023.3285943
142. A Dark Target Method for Himawari-8/AHI Aerosol Retrieval: Application and Validation B. Ge et al. 10.1109/TGRS.2018.2854743
143. Assessment of aerosol burden over Ghana K. Fosu-Amankwah et al. 10.1016/j.sciaf.2021.e00971