Articles | Volume 12, issue 8
https://doi.org/10.5194/amt-12-4619-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-12-4619-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Aug 2019
Research article |
| 30 Aug 2019
| 30 Aug 2019
Validation, comparison, and integration of GOCI, AHI, MODIS, MISR, and VIIRS aerosol optical depth over East Asia during the 2016 KORUS-AQ campaign
Department of Atmospheric Sciences, Yonsei University, Seoul, Republic
of Korea
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Hyunkwang Lim
Department of Atmospheric Sciences, Yonsei University, Seoul, Republic
of Korea
Department of Atmospheric Sciences, Yonsei University, Seoul, Republic
of Korea
Seoyoung Lee
Department of Atmospheric Sciences, Yonsei University, Seoul, Republic
of Korea
Thomas F. Eck
Universities Space Research Association, Columbia, MD, USA
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Brent N. Holben
NASA Goddard Space Flight Center, Greenbelt, MD, USA
Michael J. Garay
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Edward J. Hyer
Marine Meteorology Division, Naval Research Laboratory, Monterey, CA,
USA
Pablo E. Saide
Department of Atmospheric and Oceanic Sciences, University of California – Los Angeles, Los Angeles, CA, USA
Institute of the Environment and Sustainability, University of California – Los Angeles, Los Angeles, CA, USA
Hongqing Liu
National Oceanic and Atmospheric Administration, National
Environmental Satellite, Data, and Information Service, Center for Satellite
Applications and Research, College Park, MD, USA
I. M. Systems Group, Inc., College Park, MD, USA
Viewed
Total article views: 4,646 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 18 Mar 2019)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,013 | 1,564 | 69 | 4,646 | 82 | 87 |
- HTML: 3,013
- PDF: 1,564
- XML: 69
- Total: 4,646
- BibTeX: 82
- EndNote: 87
Total article views: 3,414 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 30 Aug 2019)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,400 | 950 | 64 | 3,414 | 78 | 79 |
- HTML: 2,400
- PDF: 950
- XML: 64
- Total: 3,414
- BibTeX: 78
- EndNote: 79
Total article views: 1,232 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 18 Mar 2019)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 613 | 614 | 5 | 1,232 | 4 | 8 |
- HTML: 613
- PDF: 614
- XML: 5
- Total: 1,232
- BibTeX: 4
- EndNote: 8
Viewed (geographical distribution)
Total article views: 4,646 (including HTML, PDF, and XML)
Thereof 4,169 with geography defined
and 477 with unknown origin.
Total article views: 3,414 (including HTML, PDF, and XML)
Thereof 3,165 with geography defined
and 249 with unknown origin.
Total article views: 1,232 (including HTML, PDF, and XML)
Thereof 1,004 with geography defined
and 228 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
69 citations as recorded by crossref.
- How is the spatiotemporal representativeness of ground- and satellite-based aerosol optical depth (AOD) measurements over Asia? L. Chen et al. 10.1016/j.atmosres.2024.107857
- The outflow of Asian biomass burning carbonaceous aerosol into the upper troposphere and lower stratosphere in spring: radiative effects seen in a global model P. Chavan et al. 10.5194/acp-21-14371-2021
- Temporal variation of surface reflectance and cloud fraction used to identify background aerosol retrieval information over East Asia S. Park et al. 10.1016/j.atmosenv.2023.119916
- Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets C. Huang et al. 10.3390/rs13163116
- Understanding and improving model representation of aerosol optical properties for a Chinese haze event measured during KORUS-AQ P. Saide et al. 10.5194/acp-20-6455-2020
- A New Cloud and Haze Mask Algorithm From Radiative Transfer Simulations Coupled With Machine Learning Y. Jiao et al. 10.1109/TGRS.2023.3252264
- Validation and Analysis of GEMS Aerosol Optical Depth Product Against AERONET over Mainland Southeast Asia B. Jang et al. 10.1007/s44408-025-00030-0
- Calibrating Geosynchronous and Polar Orbiting Satellites: Sharing Best Practices D. Helder et al. 10.3390/rs12172786
- 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
- Assessment of aerosols over five cities of Angola based on MERRA–2 reanalysis data P. Campos et al. 10.1016/j.apr.2022.101569
- Potential role of urban forest in removing PM2.5: A case study in Seoul by deep learning with satellite data A. Lee et al. 10.1016/j.uclim.2021.100795
- An Ultra‐Broadband High Efficiency Polarization Beam Splitter for High Spectral Resolution Polarimetric Imaging in the Near Infrared H. Hsiao et al. 10.1002/advs.202201227
- Carbonaceous aerosols remote sensing from geostationary satellite observation, Part I: Algorithm development using critical reflectance F. Bao et al. 10.1016/j.rse.2023.113459
- Self-adaptive bandwidth eigenvector spatial filtering model for estimating PM2.5 concentrations in the Yangtze River Delta region of China H. Tan et al. 10.1007/s11356-021-15196-4
- 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
- Simplified and Fast Atmospheric Radiative Transfer model for satellite-based aerosol optical depth retrieval X. Yan et al. 10.1016/j.atmosenv.2020.117362
- Influence of cloud, fog, and high relative humidity during pollution transport events in South Korea: Aerosol properties and PM2.5 variability T. Eck et al. 10.1016/j.atmosenv.2020.117530
- Application of a Partial Convolutional Neural Network for Estimating Geostationary Aerosol Optical Depth Data Y. Lops et al. 10.1029/2021GL093096
- Diurnal time representation of MODIS, VIIRS, MISR, and AHI over Asia and Oceania Z. Yang et al. 10.1016/j.rse.2023.113878
- Assessment of long-range transboundary aerosols in Seoul, South Korea from Geostationary Ocean Color Imager (GOCI) and ground-based observations S. Lee et al. 10.1016/j.envpol.2020.115924
- Evaluation of Machine Learning Models for Estimating PM2.5 Concentrations across Malaysia N. Zaman et al. 10.3390/app11167326
- 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
- Spatial and Temporal Variations of Aerosol Optical Thickness over the China Seas from Himawari-8 Q. Tu et al. 10.3390/rs13245082
- 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
- Temporal and spatial variations of aerosol optical properties over the Korean peninsula during KORUS-AQ Y. Choi et al. 10.1016/j.atmosenv.2021.118301
- Relating geostationary satellite measurements of aerosol optical depth (AOD) over East Asia to fine particulate matter (PM2.5): insights from the KORUS-AQ aircraft campaign and GEOS-Chem model simulations S. Zhai et al. 10.5194/acp-21-16775-2021
- Spatiotemporal estimates of daily PM2.5 concentrations based on 1-km resolution MAIAC AOD in the Beijing–Tianjin–Hebei, China X. Yang et al. 10.1016/j.envc.2022.100548
- Spatiotemporal Distributions of PM2.5 Concentrations in the Beijing–Tianjin–Hebei Region From 2013 to 2020 X. Yang et al. 10.3389/fenvs.2022.842237
- Introducing the MISR level 2 near real-time aerosol product M. Witek et al. 10.5194/amt-14-5577-2021
- Airborne observations during KORUS-AQ show that aerosol optical depths are more spatially self-consistent than aerosol intensive properties S. LeBlanc et al. 10.5194/acp-22-11275-2022
- Validation, analysis, and comparison of MISR V23 aerosol optical depth products with MODIS and AERONET observations R. Fan et al. 10.1016/j.scitotenv.2022.159117
- Validation, Analysis, and Comparison of Misr V23 Aerosol Optical Depth Products with Modis and Aeronet Observations R. Fan et al. 10.2139/ssrn.4143337
- A Geometry-Discrete Minimum Reflectance Aerosol Retrieval Algorithm (GeoMRA) for Geostationary Meteorological Satellite Over Heterogeneous Surfaces T. Zhang et al. 10.1109/TGRS.2022.3200425
- 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
- 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
- The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future L. Remer et al. 10.3390/rs12182900
- Comparison of PM2.5 in Seoul, Korea Estimated from the Various Ground-Based and Satellite AOD S. Kim et al. 10.3390/app112210755
- Estimating PM 2.5 concentrations in a central region of China using a three-stage model Y. Jing et al. 10.1080/17538947.2023.2175499
- Aerosol Optical Depth Retrieval for Sentinel-2 Based on Convolutional Neural Network Method J. Jiang et al. 10.3390/atmos14091400
- Beyond the lockdowns: satellite observations of aerosol optical depth through 2020, the first year of the COVID-19 pandemic S. Smith et al. 10.1088/1748-9326/ac7889
- Fengyun 4A Land Aerosol Retrieval: Algorithm Development, Validation, and Comparison With Other Datasets X. Su et al. 10.1109/TGRS.2023.3330544
- Revisiting the Cox and Munk wave-slope statistics using IASI observations of the sea surface C. Guérin et al. 10.1016/j.rse.2023.113508
- Estimating hourly ground-level aerosols using Geostationary Environment Monitoring Spectrometer aerosol optical depth: a machine learning approach S. O et al. 10.5194/amt-18-1471-2025
- The implication of the air quality pattern in South Korea after the COVID-19 outbreak J. Koo et al. 10.1038/s41598-020-80429-4
- Retrieval of aerosol optical properties from GOCI-II observations: Continuation of long-term geostationary aerosol monitoring over East Asia S. Lee et al. 10.1016/j.scitotenv.2023.166504
- Improved Clear Sky Model from In Situ Observations and Spatial Distribution of Aerosol Optical Depth for Satellite-Derived Solar Irradiance over the Korean Peninsula C. Kim et al. 10.3390/rs14092167
- A High-Precision Aerosol Retrieval Algorithm (HiPARA) for Advanced Himawari Imager (AHI) data: Development and verification X. Su et al. 10.1016/j.rse.2020.112221
- Multidecadal trend analysis of in situ aerosol radiative properties around the world M. Collaud Coen et al. 10.5194/acp-20-8867-2020
- Aerosol optical depth over Northeastern Brazil: A multi-platform intercomparison study G. Münchow et al. 10.1016/j.atmosres.2024.107864
- High-resolution mapping of SO2 using airborne observations from the GeoTASO instrument during the KORUS-AQ field study: PCA-based vertical column retrievals H. Chong et al. 10.1016/j.rse.2020.111725
- New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS) J. Kim et al. 10.1175/BAMS-D-18-0013.1
- Comparison of Aerosol Properties in the Korean Peninsula Between AERONET Version 2 and 3 Data Set J. Lee et al. 10.1007/s13143-020-00221-2
- Highly resolved mapping of NO2 vertical column densities from GeoTASO measurements over a megacity and industrial area during the KORUS-AQ campaign G. Choo et al. 10.5194/amt-16-625-2023
- Aerosol profiling using radiometric and polarimetric spectral measurements in the O2 near infrared bands: Estimation of information content and measurement uncertainties M. Choi et al. 10.1016/j.rse.2020.112179
- Harmonized and high-quality datasets of aerosol optical depth at a US continental site, 1997–2018 E. Kassianov et al. 10.1038/s41597-021-00866-2
- Satellite-based, top-down approach for the adjustment of aerosol precursor emissions over East Asia: the TROPOspheric Monitoring Instrument (TROPOMI) NO2 product and the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol optical depth (AOD) data fusion product and its proxy J. Park et al. 10.5194/amt-16-3039-2023
- Calibration of Maxar Constellation Over Libya-4 Site Using MAIAC Technique M. Choi et al. 10.1109/JSTARS.2024.3367250
- Simultaneous measurements of PM1 and PM10 aerosol scattering properties and their relationships in urban Beijing: A two-year observation X. Hu et al. 10.1016/j.scitotenv.2021.145215
- Evidence of haze-driven secondary production of supermicrometer aerosol nitrate and sulfate in size distribution data in South Korea J. Schlosser et al. 10.5194/acp-22-7505-2022
- Validation and Analysis of MISR and POLDER Aerosol Products over China S. Jiao et al. 10.3390/rs14153697
- Assessment of air quality in North Korea from satellite observations H. Chong et al. 10.1016/j.envint.2022.107708
- A Daytime Cloud Detection Method for Advanced Meteorological Imager Using Visible and Near-Infrared Bands Y. Choi et al. 10.1109/TGRS.2023.3327437
- Performance evaluation of MODIS and VIIRS satellite AOD products over the Indian subcontinent S. Payra et al. 10.3389/fenvs.2023.1158641
- An emerging aerosol climatology via remote sensing over Metro Manila, the Philippines G. Lorenzo et al. 10.5194/acp-23-10579-2023
- Decadal Measurements of the First Geostationary Ocean Color Satellite (GOCI) Compared with MODIS and VIIRS Data M. Park et al. 10.3390/rs14010072
- Global evaluation of Fengyun-3 MERSI dark target aerosol retrievals over land L. Yang et al. 10.1080/17538947.2024.2344580
- Fine particulate concentrations over East Asia derived from aerosols measured by the advanced Himawari Imager using machine learning Y. Cho et al. 10.1016/j.atmosres.2023.106787
- 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
- Assessing Net Growth of Phytoplankton Biomass on Hourly to Annual Time Scales Using the Geostationary Ocean Color Instrument J. Salisbury et al. 10.1029/2021GL095528
68 citations as recorded by crossref.
- How is the spatiotemporal representativeness of ground- and satellite-based aerosol optical depth (AOD) measurements over Asia? L. Chen et al. 10.1016/j.atmosres.2024.107857
- The outflow of Asian biomass burning carbonaceous aerosol into the upper troposphere and lower stratosphere in spring: radiative effects seen in a global model P. Chavan et al. 10.5194/acp-21-14371-2021
- Temporal variation of surface reflectance and cloud fraction used to identify background aerosol retrieval information over East Asia S. Park et al. 10.1016/j.atmosenv.2023.119916
- Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets C. Huang et al. 10.3390/rs13163116
- Understanding and improving model representation of aerosol optical properties for a Chinese haze event measured during KORUS-AQ P. Saide et al. 10.5194/acp-20-6455-2020
- A New Cloud and Haze Mask Algorithm From Radiative Transfer Simulations Coupled With Machine Learning Y. Jiao et al. 10.1109/TGRS.2023.3252264
- Validation and Analysis of GEMS Aerosol Optical Depth Product Against AERONET over Mainland Southeast Asia B. Jang et al. 10.1007/s44408-025-00030-0
- Calibrating Geosynchronous and Polar Orbiting Satellites: Sharing Best Practices D. Helder et al. 10.3390/rs12172786
- 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
- Assessment of aerosols over five cities of Angola based on MERRA–2 reanalysis data P. Campos et al. 10.1016/j.apr.2022.101569
- Potential role of urban forest in removing PM2.5: A case study in Seoul by deep learning with satellite data A. Lee et al. 10.1016/j.uclim.2021.100795
- An Ultra‐Broadband High Efficiency Polarization Beam Splitter for High Spectral Resolution Polarimetric Imaging in the Near Infrared H. Hsiao et al. 10.1002/advs.202201227
- Carbonaceous aerosols remote sensing from geostationary satellite observation, Part I: Algorithm development using critical reflectance F. Bao et al. 10.1016/j.rse.2023.113459
- Self-adaptive bandwidth eigenvector spatial filtering model for estimating PM2.5 concentrations in the Yangtze River Delta region of China H. Tan et al. 10.1007/s11356-021-15196-4
- 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
- Simplified and Fast Atmospheric Radiative Transfer model for satellite-based aerosol optical depth retrieval X. Yan et al. 10.1016/j.atmosenv.2020.117362
- Influence of cloud, fog, and high relative humidity during pollution transport events in South Korea: Aerosol properties and PM2.5 variability T. Eck et al. 10.1016/j.atmosenv.2020.117530
- Application of a Partial Convolutional Neural Network for Estimating Geostationary Aerosol Optical Depth Data Y. Lops et al. 10.1029/2021GL093096
- Diurnal time representation of MODIS, VIIRS, MISR, and AHI over Asia and Oceania Z. Yang et al. 10.1016/j.rse.2023.113878
- Assessment of long-range transboundary aerosols in Seoul, South Korea from Geostationary Ocean Color Imager (GOCI) and ground-based observations S. Lee et al. 10.1016/j.envpol.2020.115924
- Evaluation of Machine Learning Models for Estimating PM2.5 Concentrations across Malaysia N. Zaman et al. 10.3390/app11167326
- 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
- Spatial and Temporal Variations of Aerosol Optical Thickness over the China Seas from Himawari-8 Q. Tu et al. 10.3390/rs13245082
- 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
- Temporal and spatial variations of aerosol optical properties over the Korean peninsula during KORUS-AQ Y. Choi et al. 10.1016/j.atmosenv.2021.118301
- Relating geostationary satellite measurements of aerosol optical depth (AOD) over East Asia to fine particulate matter (PM2.5): insights from the KORUS-AQ aircraft campaign and GEOS-Chem model simulations S. Zhai et al. 10.5194/acp-21-16775-2021
- Spatiotemporal estimates of daily PM2.5 concentrations based on 1-km resolution MAIAC AOD in the Beijing–Tianjin–Hebei, China X. Yang et al. 10.1016/j.envc.2022.100548
- Spatiotemporal Distributions of PM2.5 Concentrations in the Beijing–Tianjin–Hebei Region From 2013 to 2020 X. Yang et al. 10.3389/fenvs.2022.842237
- Introducing the MISR level 2 near real-time aerosol product M. Witek et al. 10.5194/amt-14-5577-2021
- Airborne observations during KORUS-AQ show that aerosol optical depths are more spatially self-consistent than aerosol intensive properties S. LeBlanc et al. 10.5194/acp-22-11275-2022
- Validation, analysis, and comparison of MISR V23 aerosol optical depth products with MODIS and AERONET observations R. Fan et al. 10.1016/j.scitotenv.2022.159117
- Validation, Analysis, and Comparison of Misr V23 Aerosol Optical Depth Products with Modis and Aeronet Observations R. Fan et al. 10.2139/ssrn.4143337
- A Geometry-Discrete Minimum Reflectance Aerosol Retrieval Algorithm (GeoMRA) for Geostationary Meteorological Satellite Over Heterogeneous Surfaces T. Zhang et al. 10.1109/TGRS.2022.3200425
- 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
- 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
- The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future L. Remer et al. 10.3390/rs12182900
- Comparison of PM2.5 in Seoul, Korea Estimated from the Various Ground-Based and Satellite AOD S. Kim et al. 10.3390/app112210755
- Estimating PM 2.5 concentrations in a central region of China using a three-stage model Y. Jing et al. 10.1080/17538947.2023.2175499
- Aerosol Optical Depth Retrieval for Sentinel-2 Based on Convolutional Neural Network Method J. Jiang et al. 10.3390/atmos14091400
- Beyond the lockdowns: satellite observations of aerosol optical depth through 2020, the first year of the COVID-19 pandemic S. Smith et al. 10.1088/1748-9326/ac7889
- Fengyun 4A Land Aerosol Retrieval: Algorithm Development, Validation, and Comparison With Other Datasets X. Su et al. 10.1109/TGRS.2023.3330544
- Revisiting the Cox and Munk wave-slope statistics using IASI observations of the sea surface C. Guérin et al. 10.1016/j.rse.2023.113508
- Estimating hourly ground-level aerosols using Geostationary Environment Monitoring Spectrometer aerosol optical depth: a machine learning approach S. O et al. 10.5194/amt-18-1471-2025
- The implication of the air quality pattern in South Korea after the COVID-19 outbreak J. Koo et al. 10.1038/s41598-020-80429-4
- Retrieval of aerosol optical properties from GOCI-II observations: Continuation of long-term geostationary aerosol monitoring over East Asia S. Lee et al. 10.1016/j.scitotenv.2023.166504
- Improved Clear Sky Model from In Situ Observations and Spatial Distribution of Aerosol Optical Depth for Satellite-Derived Solar Irradiance over the Korean Peninsula C. Kim et al. 10.3390/rs14092167
- A High-Precision Aerosol Retrieval Algorithm (HiPARA) for Advanced Himawari Imager (AHI) data: Development and verification X. Su et al. 10.1016/j.rse.2020.112221
- Multidecadal trend analysis of in situ aerosol radiative properties around the world M. Collaud Coen et al. 10.5194/acp-20-8867-2020
- Aerosol optical depth over Northeastern Brazil: A multi-platform intercomparison study G. Münchow et al. 10.1016/j.atmosres.2024.107864
- High-resolution mapping of SO2 using airborne observations from the GeoTASO instrument during the KORUS-AQ field study: PCA-based vertical column retrievals H. Chong et al. 10.1016/j.rse.2020.111725
- New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS) J. Kim et al. 10.1175/BAMS-D-18-0013.1
- Comparison of Aerosol Properties in the Korean Peninsula Between AERONET Version 2 and 3 Data Set J. Lee et al. 10.1007/s13143-020-00221-2
- Highly resolved mapping of NO2 vertical column densities from GeoTASO measurements over a megacity and industrial area during the KORUS-AQ campaign G. Choo et al. 10.5194/amt-16-625-2023
- Aerosol profiling using radiometric and polarimetric spectral measurements in the O2 near infrared bands: Estimation of information content and measurement uncertainties M. Choi et al. 10.1016/j.rse.2020.112179
- Harmonized and high-quality datasets of aerosol optical depth at a US continental site, 1997–2018 E. Kassianov et al. 10.1038/s41597-021-00866-2
- Satellite-based, top-down approach for the adjustment of aerosol precursor emissions over East Asia: the TROPOspheric Monitoring Instrument (TROPOMI) NO2 product and the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol optical depth (AOD) data fusion product and its proxy J. Park et al. 10.5194/amt-16-3039-2023
- Calibration of Maxar Constellation Over Libya-4 Site Using MAIAC Technique M. Choi et al. 10.1109/JSTARS.2024.3367250
- Simultaneous measurements of PM1 and PM10 aerosol scattering properties and their relationships in urban Beijing: A two-year observation X. Hu et al. 10.1016/j.scitotenv.2021.145215
- Evidence of haze-driven secondary production of supermicrometer aerosol nitrate and sulfate in size distribution data in South Korea J. Schlosser et al. 10.5194/acp-22-7505-2022
- Validation and Analysis of MISR and POLDER Aerosol Products over China S. Jiao et al. 10.3390/rs14153697
- Assessment of air quality in North Korea from satellite observations H. Chong et al. 10.1016/j.envint.2022.107708
- A Daytime Cloud Detection Method for Advanced Meteorological Imager Using Visible and Near-Infrared Bands Y. Choi et al. 10.1109/TGRS.2023.3327437
- Performance evaluation of MODIS and VIIRS satellite AOD products over the Indian subcontinent S. Payra et al. 10.3389/fenvs.2023.1158641
- An emerging aerosol climatology via remote sensing over Metro Manila, the Philippines G. Lorenzo et al. 10.5194/acp-23-10579-2023
- Decadal Measurements of the First Geostationary Ocean Color Satellite (GOCI) Compared with MODIS and VIIRS Data M. Park et al. 10.3390/rs14010072
- Global evaluation of Fengyun-3 MERSI dark target aerosol retrievals over land L. Yang et al. 10.1080/17538947.2024.2344580
- Fine particulate concentrations over East Asia derived from aerosols measured by the advanced Himawari Imager using machine learning Y. Cho et al. 10.1016/j.atmosres.2023.106787
- 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
Latest update: 30 May 2025
Short summary
Satellite-based aerosol optical depth (AOD) products have been improved continuously and available from multiple low Earth orbit sensors, such as MODIS, MISR, and VIIRS, and geostationary sensors, such as GOCI and AHI, over East Asia. These multi-satellite AOD products are validated, intercompared, analyzed, and integrated to understand different characteristics, such as quality and spatio-temporal coverage, focused on several aerosol transportation cases during the 2016 KORUS-AQ campaign.
Satellite-based aerosol optical depth (AOD) products have been improved continuously and...
