Articles | Volume 16, issue 3
https://doi.org/10.5194/acp-16-1255-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-16-1255-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD retrievals against ground sunphotometer observations over East Asia
Q. Xiao
Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
H. Zhang
I.M. Systems Group Inc., College Park, MD,
USA
Department of Atmospheric Sciences, Yonsei University, Seoul, South Korea
S. Li
Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
State Key Laboratory of Remote Sensing Science, Beijing,
China
S. Kondragunta
National Oceanic and Atmospheric Administration,
Greenbelt, MD, USA
Department of Atmospheric Sciences, Yonsei University, Seoul, South Korea
B. Holben
NASA Goddard Space Flight Center, Greenbelt, MD,
USA
R. C. Levy
NASA Goddard Space Flight Center, Greenbelt, MD,
USA
Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
Viewed
Total article views: 5,078 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 03 Aug 2015)
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
2,539 | 2,401 | 138 | 5,078 | 520 | 120 | 143 |
- HTML: 2,539
- PDF: 2,401
- XML: 138
- Total: 5,078
- Supplement: 520
- BibTeX: 120
- EndNote: 143
Total article views: 4,209 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 03 Feb 2016)
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
2,245 | 1,852 | 112 | 4,209 | 318 | 97 | 118 |
- HTML: 2,245
- PDF: 1,852
- XML: 112
- Total: 4,209
- Supplement: 318
- BibTeX: 97
- EndNote: 118
Total article views: 869 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 03 Aug 2015)
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
294 | 549 | 26 | 869 | 202 | 23 | 25 |
- HTML: 294
- PDF: 549
- XML: 26
- Total: 869
- Supplement: 202
- BibTeX: 23
- EndNote: 25
Cited
105 citations as recorded by crossref.
- Comprehensive evaluation of multisource aerosol optical depth gridded products over China D. Jiang et al. 10.1016/j.atmosenv.2022.119088
- Performance of the NPP-VIIRS and aqua-MODIS Aerosol Optical Depth Products over the Yangtze River Basin L. He et al. 10.3390/rs10010117
- Spatial Factor Analysis for Aerosol Optical Depth in Metropolises in China with Regard to Spatial Heterogeneity H. Shi et al. 10.3390/atmos9040156
- High spatiotemporal resolution estimation of AOD from Himawari-8 using an ensemble machine learning gap-filling method A. Chen et al. 10.1016/j.scitotenv.2022.159673
- Analysis and research of absorbing aerosols in Beijing-Tianjin-Hebei region T. Ju et al. 10.1007/s11869-021-01151-2
- A Novel Algorithm of Haze Identification Based on FY3D/MERSI-II Remote Sensing Data Y. Si et al. 10.3390/rs15020438
- 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
- Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China D. Li et al. 10.3390/rs12060978
- Deriving Hourly PM2.5 Concentrations from Himawari-8 AODs over Beijing–Tianjin–Hebei in China W. Wang et al. 10.3390/rs9080858
- Methods, availability, and applications of PM2.5 exposure estimates derived from ground measurements, satellite, and atmospheric models M. Diao et al. 10.1080/10962247.2019.1668498
- 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
- Assimilating AOD retrievals from GOCI and VIIRS to forecast surface PM2.5 episodes over Eastern China J. Pang et al. 10.1016/j.atmosenv.2018.02.011
- 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
- A spatially structured adaptive two-stage model for retrieving ground-level PM2.5 concentrations from VIIRS AOD in China F. Yao et al. 10.1016/j.isprsjprs.2019.03.011
- Retrieval of Aerosol Optical Depth from the Himawari-8 Advanced Himawari Imager data: Application over Beijing in the summer of 2016 L. Wang et al. 10.1016/j.atmosenv.2020.117788
- Handling Missing Data in Large-Scale MODIS AOD Products Using a Two-Step Model Y. Chi et al. 10.3390/rs12223786
- An Ensemble Machine-Learning Model To Predict Historical PM2.5Concentrations in China from Satellite Data Q. Xiao et al. 10.1021/acs.est.8b02917
- Impact of the Dust Aerosol Model on the VIIRS Aerosol Optical Depth (AOD) Product across China Y. Wang et al. 10.3390/rs12060991
- Composite Aerosol Optical Depth Mapping over Northeast Asia from GEO-LEO Satellite Observations S. Ahn et al. 10.3390/rs13061096
- Application of multiplatform remote sensing data over East Asia Ocean: aerosol characteristics and aerosol types K. Luan et al. 10.1007/s11356-024-33458-9
- 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
- LGHAP: the Long-term Gap-free High-resolution Air Pollutant concentration dataset, derived via tensor-flow-based multimodal data fusion K. Bai et al. 10.5194/essd-14-907-2022
- Satellite remote sensing of aerosol optical depth: advances, challenges, and perspectives X. Wei et al. 10.1080/10643389.2019.1665944
- Collocation mismatch uncertainties in satellite aerosol retrieval validation T. Virtanen et al. 10.5194/amt-11-925-2018
- Satellite-Based Mapping of High-Resolution Ground-Level PM2.5 with VIIRS IP AOD in China through Spatially Neural Network Weighted Regression Y. Chen et al. 10.3390/rs13101979
- Absorbing Aerosol Optical Properties and Radiative Effects on Near-Surface Photochemistry in East Asia H. Chen et al. 10.3390/rs15112779
- Improving the quantification of fine particulates (PM2.5) concentrations in Malaysia using simplified and computationally efficient models N. Zaman et al. 10.1016/j.jclepro.2024.141559
- Top-Down Estimation of Particulate Matter Emissions from Extreme Tropical Peatland Fires Using Geostationary Satellite Fire Radiative Power Observations D. Fisher et al. 10.3390/s20247075
- Retrieval of Daily PM2.5 Concentrations Using Nonlinear Methods: A Case Study of the Beijing–Tianjin–Hebei Region, China L. Li et al. 10.3390/rs10122006
- Climatology and trends of aerosol optical depth with different particle size and shape in northeast China from 2001 to 2018 H. Zhao et al. 10.1016/j.scitotenv.2020.142979
- Estimating Daily PM2.5 Concentrations in Beijing Using 750-M VIIRS IP AOD Retrievals and a Nested Spatiotemporal Statistical Model F. Yao et al. 10.3390/rs11070841
- Evaluation of the NDVI-Based Pixel Selection Criteria of the MODIS C6 Dark Target and Deep Blue Combined Aerosol Product M. Bilal & J. Nichol 10.1109/JSTARS.2017.2693289
- Super-Resolution Reconstruction of Remote Sensing Data Based on Multiple Satellite Sources for Forest Fire Smoke Segmentation H. Liang et al. 10.3390/rs15174180
- Comparison of AOD from CALIPSO, MODIS, and Sun Photometer under Different Conditions over Central China B. Liu et al. 10.1038/s41598-018-28417-7
- Exploring the spatial-temporal characteristics of the aerosol optical depth (AOD) in Central Asia based on the moderate resolution imaging spectroradiometer (MODIS) D. Wang et al. 10.1007/s10661-020-08299-x
- Validation of MODIS and VIIRS derived aerosol optical depth over complex coastal waters M. Bilal et al. 10.1016/j.atmosres.2016.11.009
- Evaluation of the MISR fine resolution aerosol product using MODIS, MISR, and ground observations over China Y. Si et al. 10.1016/j.atmosenv.2019.117229
- Air pollution scenario over Pakistan: Characterization and ranking of extremely polluted cities using long-term concentrations of aerosols and trace gases M. Bilal et al. 10.1016/j.rse.2021.112617
- The Spatiotemporal Pattern of the Aerosol Optical Depth (AOD) on the Canopies of Various Forest Types in the Exurban National Park: A Case in Ningbo City, Eastern China Y. Chi et al. 10.1155/2019/4942827
- 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
- An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks B. Holben et al. 10.5194/acp-18-655-2018
- Long-term spatiotemporal variations of aerosol optical depth over Yellow and Bohai Sea X. Shen et al. 10.1007/s11356-019-04203-4
- Fine resolution air quality dynamics related to socioeconomic and land use factors in the most polluted desert metropolitan in the American Southwest Y. Li & S. Myint 10.1016/j.scitotenv.2021.147713
- Evaluation and Comparison of Long-Term MODIS C5.1 and C6 Products against AERONET Observations over China A. Fan et al. 10.3390/rs9121269
- 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
- FY-4A/AGRI Aerosol Optical Depth Retrieval Capability Test and Validation Based on NNAeroG H. Ding et al. 10.3390/rs14215591
- Predicting ground-level PM2.5 concentrations in the Beijing-Tianjin-Hebei region: A hybrid remote sensing and machine learning approach X. Li & X. Zhang 10.1016/j.envpol.2019.03.068
- Evaluation of Himawari-8 version 2.0 aerosol products against AERONET ground-based measurements over central and northern China L. Wang et al. 10.1016/j.atmosenv.2020.117357
- Improving aerosol optical depth retrievals from Himawari-8 with ensemble learning enhancement: Validation over Asia D. Fu et al. 10.1016/j.atmosres.2023.106624
- Evaluating temporal and spatial variability and trend of aerosol optical depth (550 nm) over Iran using data from MODIS on board the Terra and Aqua satellites A. Dadashi-Roudbari & M. Ahmadi 10.1007/s12517-020-5232-0
- Evaluation of VIIRS Land Aerosol Model Selection with AERONET Measurements W. Wang et al. 10.3390/ijerph14091016
- Exploring the trend, prediction and driving forces of aerosols using satellite and ground data, and implications for climate change mitigation X. Li et al. 10.1016/j.jclepro.2019.03.121
- Decoupling between PM2.5 concentrations and aerosol optical depth at ground stations in China W. Fu et al. 10.3389/fenvs.2022.979918
- Advancing application of satellite remote sensing technologies for linking atmospheric and built environment to health Y. Tian et al. 10.3389/fpubh.2023.1270033
- A full-coverage estimation of PM2.5 concentrations using a hybrid XGBoost-WD model and WRF-simulated meteorological fields in the Yangtze River Delta Urban Agglomeration, China J. Wang et al. 10.1016/j.envres.2021.111799
- A Characteristic Analysis of Various Air Pollutants and Their Correlation with O3 in the Jiangsu, Shandong, Henan, and Anhui Provinces of China T. Ju et al. 10.3390/su142113737
- An Evaluation of Four MODIS Collection 6 Aerosol Products in a Humid Subtropical Region M. Zhang et al. 10.3390/rs9111173
- Diurnal time representation of MODIS, VIIRS, MISR, and AHI over Asia and Oceania Z. Yang et al. 10.1016/j.rse.2023.113878
- Atmospheric Aerosol Over Ukraine Region: Current Status of Knowledge and Research Efforts G. Milinevsky & V. Danylevsky 10.3389/fenvs.2018.00059
- Estimating Spatio-Temporal Variations of PM2.5 Concentrations Using VIIRS-Derived AOD in the Guanzhong Basin, China K. Zhang et al. 10.3390/rs11222679
- 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
- An exploratory study on the aerosol height retrieval from OMI measurements of the 477 nm O<sub>2</sub> − O<sub>2</sub> spectral band using a neural network approach J. Chimot et al. 10.5194/amt-10-783-2017
- Performance evaluation of MODIS and VIIRS satellite AOD products over the Indian subcontinent S. Payra et al. 10.3389/fenvs.2023.1158641
- Absorbable aerosols based on OMI data: a case study in three provinces of Northeast China J. Duan et al. 10.1007/s10661-021-09249-x
- High-Resolution Planetscope Imagery and Machine Learning for Estimating Suspended Particulate Matter in the Ebinur Lake, Xinjiang, China P. Duan et al. 10.1109/JSTARS.2022.3233113
- 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
- Overview of atmospheric aerosol studies in Malaysia: Known and unknown K. Kanniah et al. 10.1016/j.atmosres.2016.08.002
- Associations between birth outcomes and maternal PM2.5 exposure in Shanghai: A comparison of three exposure assessment approaches Q. Xiao et al. 10.1016/j.envint.2018.04.050
- Analysis of Remote Sensing Monitoring of Atmospheric Ozone in Japan from 2010 to 2021 S. Lei et al. 10.1007/s11270-023-06586-0
- Evaluation and uncertainty analysis of Himawari-8 hourly aerosol product version 3.1 and its influence on surface solar radiation before and during the COVID-19 outbreak C. Tang et al. 10.1016/j.scitotenv.2023.164456
- 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
- Evaluation and Comparison of Multi-Satellite Aerosol Optical Depth Products over East Asia Ocean Z. Cao et al. 10.3390/toxics11100813
- A comparative time series analysis and modeling of aerosols in the contiguous United States and China X. Li et al. 10.1016/j.scitotenv.2019.07.072
- Evaluation of LJ1-01 Nighttime Light Imagery for Estimating Monthly PM2.5 Concentration: A Comparison With NPP-VIIRS Nighttime Light Data G. Zhang et al. 10.1109/JSTARS.2020.3002671
- Atmospheric aerosol pollution across China: a spatiotemporal analysis of satellite-based aerosol optical depth during 2000–2016 Y. Feng et al. 10.1080/17538947.2018.1486892
- An Adaptive Dark-Target Algorithm for Retrieving Land AOD Applied to FY-4B/AGRI Data Y. Si et al. 10.1109/JSTARS.2024.3408251
- Long-term (2006–2015) variations and relations of multiple atmospheric pollutants based on multi-remote sensing data over the North China Plain Y. Si et al. 10.1016/j.envpol.2019.113323
- Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns G. de Leeuw et al. 10.5194/acp-18-1573-2018
- Synergistic data fusion of multimodal AOD and air quality data for near real-time full coverage air pollution assessment K. Li et al. 10.1016/j.jenvman.2021.114121
- Validation of VIIRS AOD through a Comparison with a Sun Photometer and MODIS AODs over Wuhan W. Wang et al. 10.3390/rs9050403
- An Estimation of Daily PM2.5 Concentration in Thailand Using Satellite Data at 1-Kilometer Resolution S. Buya et al. 10.3390/su151310024
- 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
- 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
- Generating Hourly Fine Seamless Aerosol Optical Depth Products by Fusing Multiple Satellite and Numerical Model Data B. Zou et al. 10.1109/TGRS.2024.3385397
- Impacts of snow and cloud covers on satellite-derived PM2.5 levels J. Bi et al. 10.1016/j.rse.2018.12.002
- Satellite-based estimation of hourly PM2.5 levels during heavy winter pollution episodes in the Yangtze River Delta, China Q. She et al. 10.1016/j.chemosphere.2019.124678
- Advances in the estimation of high Spatio-temporal resolution pan-African top-down biomass burning emissions made using geostationary fire radiative power (FRP) and MAIAC aerosol optical depth (AOD) data H. Nguyen & M. Wooster 10.1016/j.rse.2020.111971
- A multidimensional comparison between MODIS and VIIRS AOD in estimating ground-level PM2.5 concentrations over a heavily polluted region in China F. Yao et al. 10.1016/j.scitotenv.2017.08.209
- Improving air quality forecasting with the assimilation of GOCI aerosol optical depth (AOD) retrievals during the KORUS-AQ period S. Ha et al. 10.5194/acp-20-6015-2020
- Research progress, challenges, and prospects of PM2.5 concentration estimation using satellite data S. Zhu et al. 10.1139/er-2022-0125
- Evaluation of gap-filling approaches in satellite-based daily PM2.5 prediction models Q. Xiao et al. 10.1016/j.atmosenv.2020.117921
- The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future L. Remer et al. 10.3390/rs12182900
- A comparative study of EOF and NMF analysis on downward trend of AOD over China from 2011 to 2019 Q. Ma et al. 10.1016/j.envpol.2021.117713
- Controlling factors analysis for the Himawari-8 aerosol optical depth accuracy from the standpoint of size distribution, solar zenith angles and scattering angles M. Zhang et al. 10.1016/j.atmosenv.2020.117501
- Estimation of health benefits from air quality improvement using the MODIS AOD dataset in Seoul, Korea D. Kim et al. 10.1016/j.envres.2019.03.042
- Verification, improvement and application of aerosol optical depths in China Part 1: Inter-comparison of NPP-VIIRS and Aqua-MODIS J. Wei et al. 10.1016/j.atmosenv.2017.11.048
- GOCI-II geostationary satellite hourly aerosol optical depth obtained by data-driven methods: Validation and comparison Y. Fan et al. 10.1016/j.atmosenv.2023.119965
- Impact of environmental pollution on the retrieval of AOD products from Visible Infrared Imaging Radiometer Suite (VIIRS) over wuhan Y. Ma et al. 10.1016/j.apr.2019.09.014
- Evaluation of the Aqua-MODIS C6 and C6.1 Aerosol Optical Depth Products in the Yellow River Basin, China M. Zhang et al. 10.3390/atmos10080426
- 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
- Long-term variation of aerosol optical properties associated with aerosol types over East Asia using AERONET and satellite (VIIRS, OMI) data (2012–2019) S. Eom et al. 10.1016/j.atmosres.2022.106457
- 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
- 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. 10.1007/s11356-018-2290-x
- Evaluation and Comparison of Himawari-8 L2 V1.0, V2.1 and MODIS C6.1 aerosol products over Asia and the oceania regions X. Yang et al. 10.1016/j.atmosenv.2019.117068
- Evaluation of Machine Learning Models for Estimating PM2.5 Concentrations across Malaysia N. Zaman et al. 10.3390/app11167326
102 citations as recorded by crossref.
- Comprehensive evaluation of multisource aerosol optical depth gridded products over China D. Jiang et al. 10.1016/j.atmosenv.2022.119088
- Performance of the NPP-VIIRS and aqua-MODIS Aerosol Optical Depth Products over the Yangtze River Basin L. He et al. 10.3390/rs10010117
- Spatial Factor Analysis for Aerosol Optical Depth in Metropolises in China with Regard to Spatial Heterogeneity H. Shi et al. 10.3390/atmos9040156
- High spatiotemporal resolution estimation of AOD from Himawari-8 using an ensemble machine learning gap-filling method A. Chen et al. 10.1016/j.scitotenv.2022.159673
- Analysis and research of absorbing aerosols in Beijing-Tianjin-Hebei region T. Ju et al. 10.1007/s11869-021-01151-2
- A Novel Algorithm of Haze Identification Based on FY3D/MERSI-II Remote Sensing Data Y. Si et al. 10.3390/rs15020438
- 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
- Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China D. Li et al. 10.3390/rs12060978
- Deriving Hourly PM2.5 Concentrations from Himawari-8 AODs over Beijing–Tianjin–Hebei in China W. Wang et al. 10.3390/rs9080858
- Methods, availability, and applications of PM2.5 exposure estimates derived from ground measurements, satellite, and atmospheric models M. Diao et al. 10.1080/10962247.2019.1668498
- 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
- Assimilating AOD retrievals from GOCI and VIIRS to forecast surface PM2.5 episodes over Eastern China J. Pang et al. 10.1016/j.atmosenv.2018.02.011
- 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
- A spatially structured adaptive two-stage model for retrieving ground-level PM2.5 concentrations from VIIRS AOD in China F. Yao et al. 10.1016/j.isprsjprs.2019.03.011
- Retrieval of Aerosol Optical Depth from the Himawari-8 Advanced Himawari Imager data: Application over Beijing in the summer of 2016 L. Wang et al. 10.1016/j.atmosenv.2020.117788
- Handling Missing Data in Large-Scale MODIS AOD Products Using a Two-Step Model Y. Chi et al. 10.3390/rs12223786
- An Ensemble Machine-Learning Model To Predict Historical PM2.5Concentrations in China from Satellite Data Q. Xiao et al. 10.1021/acs.est.8b02917
- Impact of the Dust Aerosol Model on the VIIRS Aerosol Optical Depth (AOD) Product across China Y. Wang et al. 10.3390/rs12060991
- Composite Aerosol Optical Depth Mapping over Northeast Asia from GEO-LEO Satellite Observations S. Ahn et al. 10.3390/rs13061096
- Application of multiplatform remote sensing data over East Asia Ocean: aerosol characteristics and aerosol types K. Luan et al. 10.1007/s11356-024-33458-9
- 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
- LGHAP: the Long-term Gap-free High-resolution Air Pollutant concentration dataset, derived via tensor-flow-based multimodal data fusion K. Bai et al. 10.5194/essd-14-907-2022
- Satellite remote sensing of aerosol optical depth: advances, challenges, and perspectives X. Wei et al. 10.1080/10643389.2019.1665944
- Collocation mismatch uncertainties in satellite aerosol retrieval validation T. Virtanen et al. 10.5194/amt-11-925-2018
- Satellite-Based Mapping of High-Resolution Ground-Level PM2.5 with VIIRS IP AOD in China through Spatially Neural Network Weighted Regression Y. Chen et al. 10.3390/rs13101979
- Absorbing Aerosol Optical Properties and Radiative Effects on Near-Surface Photochemistry in East Asia H. Chen et al. 10.3390/rs15112779
- Improving the quantification of fine particulates (PM2.5) concentrations in Malaysia using simplified and computationally efficient models N. Zaman et al. 10.1016/j.jclepro.2024.141559
- Top-Down Estimation of Particulate Matter Emissions from Extreme Tropical Peatland Fires Using Geostationary Satellite Fire Radiative Power Observations D. Fisher et al. 10.3390/s20247075
- Retrieval of Daily PM2.5 Concentrations Using Nonlinear Methods: A Case Study of the Beijing–Tianjin–Hebei Region, China L. Li et al. 10.3390/rs10122006
- Climatology and trends of aerosol optical depth with different particle size and shape in northeast China from 2001 to 2018 H. Zhao et al. 10.1016/j.scitotenv.2020.142979
- Estimating Daily PM2.5 Concentrations in Beijing Using 750-M VIIRS IP AOD Retrievals and a Nested Spatiotemporal Statistical Model F. Yao et al. 10.3390/rs11070841
- Evaluation of the NDVI-Based Pixel Selection Criteria of the MODIS C6 Dark Target and Deep Blue Combined Aerosol Product M. Bilal & J. Nichol 10.1109/JSTARS.2017.2693289
- Super-Resolution Reconstruction of Remote Sensing Data Based on Multiple Satellite Sources for Forest Fire Smoke Segmentation H. Liang et al. 10.3390/rs15174180
- Comparison of AOD from CALIPSO, MODIS, and Sun Photometer under Different Conditions over Central China B. Liu et al. 10.1038/s41598-018-28417-7
- Exploring the spatial-temporal characteristics of the aerosol optical depth (AOD) in Central Asia based on the moderate resolution imaging spectroradiometer (MODIS) D. Wang et al. 10.1007/s10661-020-08299-x
- Validation of MODIS and VIIRS derived aerosol optical depth over complex coastal waters M. Bilal et al. 10.1016/j.atmosres.2016.11.009
- Evaluation of the MISR fine resolution aerosol product using MODIS, MISR, and ground observations over China Y. Si et al. 10.1016/j.atmosenv.2019.117229
- Air pollution scenario over Pakistan: Characterization and ranking of extremely polluted cities using long-term concentrations of aerosols and trace gases M. Bilal et al. 10.1016/j.rse.2021.112617
- The Spatiotemporal Pattern of the Aerosol Optical Depth (AOD) on the Canopies of Various Forest Types in the Exurban National Park: A Case in Ningbo City, Eastern China Y. Chi et al. 10.1155/2019/4942827
- 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
- An overview of mesoscale aerosol processes, comparisons, and validation studies from DRAGON networks B. Holben et al. 10.5194/acp-18-655-2018
- Long-term spatiotemporal variations of aerosol optical depth over Yellow and Bohai Sea X. Shen et al. 10.1007/s11356-019-04203-4
- Fine resolution air quality dynamics related to socioeconomic and land use factors in the most polluted desert metropolitan in the American Southwest Y. Li & S. Myint 10.1016/j.scitotenv.2021.147713
- Evaluation and Comparison of Long-Term MODIS C5.1 and C6 Products against AERONET Observations over China A. Fan et al. 10.3390/rs9121269
- 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
- FY-4A/AGRI Aerosol Optical Depth Retrieval Capability Test and Validation Based on NNAeroG H. Ding et al. 10.3390/rs14215591
- Predicting ground-level PM2.5 concentrations in the Beijing-Tianjin-Hebei region: A hybrid remote sensing and machine learning approach X. Li & X. Zhang 10.1016/j.envpol.2019.03.068
- Evaluation of Himawari-8 version 2.0 aerosol products against AERONET ground-based measurements over central and northern China L. Wang et al. 10.1016/j.atmosenv.2020.117357
- Improving aerosol optical depth retrievals from Himawari-8 with ensemble learning enhancement: Validation over Asia D. Fu et al. 10.1016/j.atmosres.2023.106624
- Evaluating temporal and spatial variability and trend of aerosol optical depth (550 nm) over Iran using data from MODIS on board the Terra and Aqua satellites A. Dadashi-Roudbari & M. Ahmadi 10.1007/s12517-020-5232-0
- Evaluation of VIIRS Land Aerosol Model Selection with AERONET Measurements W. Wang et al. 10.3390/ijerph14091016
- Exploring the trend, prediction and driving forces of aerosols using satellite and ground data, and implications for climate change mitigation X. Li et al. 10.1016/j.jclepro.2019.03.121
- Decoupling between PM2.5 concentrations and aerosol optical depth at ground stations in China W. Fu et al. 10.3389/fenvs.2022.979918
- Advancing application of satellite remote sensing technologies for linking atmospheric and built environment to health Y. Tian et al. 10.3389/fpubh.2023.1270033
- A full-coverage estimation of PM2.5 concentrations using a hybrid XGBoost-WD model and WRF-simulated meteorological fields in the Yangtze River Delta Urban Agglomeration, China J. Wang et al. 10.1016/j.envres.2021.111799
- A Characteristic Analysis of Various Air Pollutants and Their Correlation with O3 in the Jiangsu, Shandong, Henan, and Anhui Provinces of China T. Ju et al. 10.3390/su142113737
- An Evaluation of Four MODIS Collection 6 Aerosol Products in a Humid Subtropical Region M. Zhang et al. 10.3390/rs9111173
- Diurnal time representation of MODIS, VIIRS, MISR, and AHI over Asia and Oceania Z. Yang et al. 10.1016/j.rse.2023.113878
- Atmospheric Aerosol Over Ukraine Region: Current Status of Knowledge and Research Efforts G. Milinevsky & V. Danylevsky 10.3389/fenvs.2018.00059
- Estimating Spatio-Temporal Variations of PM2.5 Concentrations Using VIIRS-Derived AOD in the Guanzhong Basin, China K. Zhang et al. 10.3390/rs11222679
- 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
- An exploratory study on the aerosol height retrieval from OMI measurements of the 477 nm O<sub>2</sub> − O<sub>2</sub> spectral band using a neural network approach J. Chimot et al. 10.5194/amt-10-783-2017
- Performance evaluation of MODIS and VIIRS satellite AOD products over the Indian subcontinent S. Payra et al. 10.3389/fenvs.2023.1158641
- Absorbable aerosols based on OMI data: a case study in three provinces of Northeast China J. Duan et al. 10.1007/s10661-021-09249-x
- High-Resolution Planetscope Imagery and Machine Learning for Estimating Suspended Particulate Matter in the Ebinur Lake, Xinjiang, China P. Duan et al. 10.1109/JSTARS.2022.3233113
- 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
- Overview of atmospheric aerosol studies in Malaysia: Known and unknown K. Kanniah et al. 10.1016/j.atmosres.2016.08.002
- Associations between birth outcomes and maternal PM2.5 exposure in Shanghai: A comparison of three exposure assessment approaches Q. Xiao et al. 10.1016/j.envint.2018.04.050
- Analysis of Remote Sensing Monitoring of Atmospheric Ozone in Japan from 2010 to 2021 S. Lei et al. 10.1007/s11270-023-06586-0
- Evaluation and uncertainty analysis of Himawari-8 hourly aerosol product version 3.1 and its influence on surface solar radiation before and during the COVID-19 outbreak C. Tang et al. 10.1016/j.scitotenv.2023.164456
- 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
- Evaluation and Comparison of Multi-Satellite Aerosol Optical Depth Products over East Asia Ocean Z. Cao et al. 10.3390/toxics11100813
- A comparative time series analysis and modeling of aerosols in the contiguous United States and China X. Li et al. 10.1016/j.scitotenv.2019.07.072
- Evaluation of LJ1-01 Nighttime Light Imagery for Estimating Monthly PM2.5 Concentration: A Comparison With NPP-VIIRS Nighttime Light Data G. Zhang et al. 10.1109/JSTARS.2020.3002671
- Atmospheric aerosol pollution across China: a spatiotemporal analysis of satellite-based aerosol optical depth during 2000–2016 Y. Feng et al. 10.1080/17538947.2018.1486892
- An Adaptive Dark-Target Algorithm for Retrieving Land AOD Applied to FY-4B/AGRI Data Y. Si et al. 10.1109/JSTARS.2024.3408251
- Long-term (2006–2015) variations and relations of multiple atmospheric pollutants based on multi-remote sensing data over the North China Plain Y. Si et al. 10.1016/j.envpol.2019.113323
- Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns G. de Leeuw et al. 10.5194/acp-18-1573-2018
- Synergistic data fusion of multimodal AOD and air quality data for near real-time full coverage air pollution assessment K. Li et al. 10.1016/j.jenvman.2021.114121
- Validation of VIIRS AOD through a Comparison with a Sun Photometer and MODIS AODs over Wuhan W. Wang et al. 10.3390/rs9050403
- An Estimation of Daily PM2.5 Concentration in Thailand Using Satellite Data at 1-Kilometer Resolution S. Buya et al. 10.3390/su151310024
- 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
- 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
- Generating Hourly Fine Seamless Aerosol Optical Depth Products by Fusing Multiple Satellite and Numerical Model Data B. Zou et al. 10.1109/TGRS.2024.3385397
- Impacts of snow and cloud covers on satellite-derived PM2.5 levels J. Bi et al. 10.1016/j.rse.2018.12.002
- Satellite-based estimation of hourly PM2.5 levels during heavy winter pollution episodes in the Yangtze River Delta, China Q. She et al. 10.1016/j.chemosphere.2019.124678
- Advances in the estimation of high Spatio-temporal resolution pan-African top-down biomass burning emissions made using geostationary fire radiative power (FRP) and MAIAC aerosol optical depth (AOD) data H. Nguyen & M. Wooster 10.1016/j.rse.2020.111971
- A multidimensional comparison between MODIS and VIIRS AOD in estimating ground-level PM2.5 concentrations over a heavily polluted region in China F. Yao et al. 10.1016/j.scitotenv.2017.08.209
- Improving air quality forecasting with the assimilation of GOCI aerosol optical depth (AOD) retrievals during the KORUS-AQ period S. Ha et al. 10.5194/acp-20-6015-2020
- Research progress, challenges, and prospects of PM2.5 concentration estimation using satellite data S. Zhu et al. 10.1139/er-2022-0125
- Evaluation of gap-filling approaches in satellite-based daily PM2.5 prediction models Q. Xiao et al. 10.1016/j.atmosenv.2020.117921
- The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future L. Remer et al. 10.3390/rs12182900
- A comparative study of EOF and NMF analysis on downward trend of AOD over China from 2011 to 2019 Q. Ma et al. 10.1016/j.envpol.2021.117713
- Controlling factors analysis for the Himawari-8 aerosol optical depth accuracy from the standpoint of size distribution, solar zenith angles and scattering angles M. Zhang et al. 10.1016/j.atmosenv.2020.117501
- Estimation of health benefits from air quality improvement using the MODIS AOD dataset in Seoul, Korea D. Kim et al. 10.1016/j.envres.2019.03.042
- Verification, improvement and application of aerosol optical depths in China Part 1: Inter-comparison of NPP-VIIRS and Aqua-MODIS J. Wei et al. 10.1016/j.atmosenv.2017.11.048
- GOCI-II geostationary satellite hourly aerosol optical depth obtained by data-driven methods: Validation and comparison Y. Fan et al. 10.1016/j.atmosenv.2023.119965
- Impact of environmental pollution on the retrieval of AOD products from Visible Infrared Imaging Radiometer Suite (VIIRS) over wuhan Y. Ma et al. 10.1016/j.apr.2019.09.014
- Evaluation of the Aqua-MODIS C6 and C6.1 Aerosol Optical Depth Products in the Yellow River Basin, China M. Zhang et al. 10.3390/atmos10080426
- 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
- Long-term variation of aerosol optical properties associated with aerosol types over East Asia using AERONET and satellite (VIIRS, OMI) data (2012–2019) S. Eom et al. 10.1016/j.atmosres.2022.106457
- 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
3 citations as recorded by crossref.
- 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. 10.1007/s11356-018-2290-x
- Evaluation and Comparison of Himawari-8 L2 V1.0, V2.1 and MODIS C6.1 aerosol products over Asia and the oceania regions X. Yang et al. 10.1016/j.atmosenv.2019.117068
- Evaluation of Machine Learning Models for Estimating PM2.5 Concentrations across Malaysia N. Zaman et al. 10.3390/app11167326
Saved (preprint)
Latest update: 21 Nov 2024
Short summary
Using ground AOD measurements from AERONET, DRAGON-Asia Campaign, and handheld sunphotometers, we evaluated emerging aerosol products from VIIRS, GOCI, and Terra and Aqua MODIS (Collection 6) in East Asia in 2012–2013. We found that satellite aerosol products performed better in tracking the day-to-day variability than the high-resolution spatial variability. VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and MODIS C6 3 km products had positive biases.
Using ground AOD measurements from AERONET, DRAGON-Asia Campaign, and handheld sunphotometers,...
Altmetrics
Final-revised paper
Preprint