Articles | Volume 11, issue 23
Atmos. Chem. Phys., 11, 11977–11991, 2011
https://doi.org/10.5194/acp-11-11977-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 11, 11977–11991, 2011
https://doi.org/10.5194/acp-11-11977-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
02 Dec 2011
Research article
| 02 Dec 2011
A multi-angle aerosol optical depth retrieval algorithm for geostationary satellite data over the United States
H. Zhang et al.
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Cited
26 citations as recorded by crossref.
- Nighttime smoke aerosol optical depth over U.S. rural areas: First retrieval from VIIRS moonlight observations M. Zhou et al. 10.1016/j.rse.2021.112717
- Aerosol optical properties derived from the DRAGON-NE Asia campaign, and implications for a single-channel algorithm to retrieve aerosol optical depth in spring from Meteorological Imager (MI) on-board the Communication, Ocean, and Meteorological Satellite (COMS) M. Kim et al. 10.5194/acp-16-1789-2016
- Application of low-cost fine particulate mass monitors to convert satellite aerosol optical depth to surface concentrations in North America and Africa C. Malings et al. 10.5194/amt-13-3873-2020
- Spectral and diurnal temporal suitability of GOES Advanced Baseline Imager (ABI) reflectance for burned area mapping D. Roy et al. 10.1016/j.jag.2020.102271
- Using Machine Learning to Estimate Global PM2.5 for Environmental Health Studies D. Lary et al. 10.4137/EHI.S15664
- Assessment of Aerosol optical depth under background and polluted conditions using AERONET and VIIRS datasets M. Kim et al. 10.1016/j.atmosenv.2020.117994
- Joint Retrieval of Aerosol Optical Depth and Surface Reflectance Over Land Using Geostationary Satellite Data L. She et al. 10.1109/TGRS.2018.2867000
- Estimation of the Hourly Aerosol Optical Depth From GOCI Geostationary Satellite Data: Deep Neural Network, Machine Learning, and Physical Models J. Yeom et al. 10.1109/TGRS.2021.3107542
- A simplified aerosol retrieval algorithm for Himawari-8 Advanced Himawari Imager over Beijing Z. Zhang et al. 10.1016/j.atmosenv.2018.11.023
- Aerosol optical depth (AOD) retrieval using simultaneous GOES-East and GOES-West reflected radiances over the western United States H. Zhang et al. 10.5194/amt-6-471-2013
- Machine Learning Approach To Estimate Hourly Exposure to Fine Particulate Matter for Urban, Rural, and Remote Populations during Wildfire Seasons J. Yao et al. 10.1021/acs.est.8b01921
- Consistent retrieval of multiple parameters from GOES-R top of atmosphere reflectance data H. Xiong et al. 10.1080/01431161.2020.1766151
- Improving the Estimation of Daily Aerosol Optical Depth and Aerosol Radiative Effect Using an Optimized Artificial Neural Network W. Qin et al. 10.3390/rs10071022
- A Dark Target Algorithm for the GOSAT TANSO-CAI Sensor in Aerosol Optical Depth Retrieval over Land G. Zhong et al. 10.3390/rs9060524
- Global observations of aerosol-cloud-precipitation-climate interactions D. Rosenfeld et al. 10.1002/2013RG000441
- Holistics 3.0 for Health D. Lary et al. 10.3390/ijgi3031023
- Deriving a Global and Hourly Data Set of Aerosol Optical Depth Over Land Using Data From Four Geostationary Satellites: GOES-16, MSG-1, MSG-4, and Himawari-8 Y. Xie et al. 10.1109/TGRS.2019.2944949
- Aerosol Optical Depth Retrieval over East Asia Using Himawari-8/AHI Data W. Zhang et al. 10.3390/rs10010137
- GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign M. Choi et al. 10.5194/amt-9-1377-2016
- Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization C. Jin et al. 10.3390/rs13224689
- Satellite remote sensing of aerosol optical depth: advances, challenges, and perspectives X. Wei et al. 10.1080/10643389.2019.1665944
- Utilization of O<sub>4</sub> slant column density to derive aerosol layer height from a space-borne UV–visible hyperspectral sensor: sensitivity and case study S. Park et al. 10.5194/acp-16-1987-2016
- Assessment of Himawari-8 AHI Aerosol Optical Depth Over Land W. Zhang et al. 10.3390/rs11091108
- Validating and Comparing Highly Resolved Commercial “Off the Shelf” PM Monitoring Sensors with Satellite Based Hybrid Models, for Improved Environmental Exposure Assessment D. Lesser et al. 10.3390/s21010063
- Assessing the Potential of Geostationary Satellites for Aerosol Remote Sensing Based on Critical Surface Albedo X. Ceamanos et al. 10.3390/rs11242958
- Improvement of aerosol optical depth retrieval over Hong Kong from a geostationary meteorological satellite using critical reflectance with background optical depth correction M. Kim et al. 10.1016/j.rse.2013.12.003
26 citations as recorded by crossref.
- Nighttime smoke aerosol optical depth over U.S. rural areas: First retrieval from VIIRS moonlight observations M. Zhou et al. 10.1016/j.rse.2021.112717
- Aerosol optical properties derived from the DRAGON-NE Asia campaign, and implications for a single-channel algorithm to retrieve aerosol optical depth in spring from Meteorological Imager (MI) on-board the Communication, Ocean, and Meteorological Satellite (COMS) M. Kim et al. 10.5194/acp-16-1789-2016
- Application of low-cost fine particulate mass monitors to convert satellite aerosol optical depth to surface concentrations in North America and Africa C. Malings et al. 10.5194/amt-13-3873-2020
- Spectral and diurnal temporal suitability of GOES Advanced Baseline Imager (ABI) reflectance for burned area mapping D. Roy et al. 10.1016/j.jag.2020.102271
- Using Machine Learning to Estimate Global PM2.5 for Environmental Health Studies D. Lary et al. 10.4137/EHI.S15664
- Assessment of Aerosol optical depth under background and polluted conditions using AERONET and VIIRS datasets M. Kim et al. 10.1016/j.atmosenv.2020.117994
- Joint Retrieval of Aerosol Optical Depth and Surface Reflectance Over Land Using Geostationary Satellite Data L. She et al. 10.1109/TGRS.2018.2867000
- Estimation of the Hourly Aerosol Optical Depth From GOCI Geostationary Satellite Data: Deep Neural Network, Machine Learning, and Physical Models J. Yeom et al. 10.1109/TGRS.2021.3107542
- A simplified aerosol retrieval algorithm for Himawari-8 Advanced Himawari Imager over Beijing Z. Zhang et al. 10.1016/j.atmosenv.2018.11.023
- Aerosol optical depth (AOD) retrieval using simultaneous GOES-East and GOES-West reflected radiances over the western United States H. Zhang et al. 10.5194/amt-6-471-2013
- Machine Learning Approach To Estimate Hourly Exposure to Fine Particulate Matter for Urban, Rural, and Remote Populations during Wildfire Seasons J. Yao et al. 10.1021/acs.est.8b01921
- Consistent retrieval of multiple parameters from GOES-R top of atmosphere reflectance data H. Xiong et al. 10.1080/01431161.2020.1766151
- Improving the Estimation of Daily Aerosol Optical Depth and Aerosol Radiative Effect Using an Optimized Artificial Neural Network W. Qin et al. 10.3390/rs10071022
- A Dark Target Algorithm for the GOSAT TANSO-CAI Sensor in Aerosol Optical Depth Retrieval over Land G. Zhong et al. 10.3390/rs9060524
- Global observations of aerosol-cloud-precipitation-climate interactions D. Rosenfeld et al. 10.1002/2013RG000441
- Holistics 3.0 for Health D. Lary et al. 10.3390/ijgi3031023
- Deriving a Global and Hourly Data Set of Aerosol Optical Depth Over Land Using Data From Four Geostationary Satellites: GOES-16, MSG-1, MSG-4, and Himawari-8 Y. Xie et al. 10.1109/TGRS.2019.2944949
- Aerosol Optical Depth Retrieval over East Asia Using Himawari-8/AHI Data W. Zhang et al. 10.3390/rs10010137
- GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign M. Choi et al. 10.5194/amt-9-1377-2016
- Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization C. Jin et al. 10.3390/rs13224689
- Satellite remote sensing of aerosol optical depth: advances, challenges, and perspectives X. Wei et al. 10.1080/10643389.2019.1665944
- Utilization of O<sub>4</sub> slant column density to derive aerosol layer height from a space-borne UV–visible hyperspectral sensor: sensitivity and case study S. Park et al. 10.5194/acp-16-1987-2016
- Assessment of Himawari-8 AHI Aerosol Optical Depth Over Land W. Zhang et al. 10.3390/rs11091108
- Validating and Comparing Highly Resolved Commercial “Off the Shelf” PM Monitoring Sensors with Satellite Based Hybrid Models, for Improved Environmental Exposure Assessment D. Lesser et al. 10.3390/s21010063
- Assessing the Potential of Geostationary Satellites for Aerosol Remote Sensing Based on Critical Surface Albedo X. Ceamanos et al. 10.3390/rs11242958
- Improvement of aerosol optical depth retrieval over Hong Kong from a geostationary meteorological satellite using critical reflectance with background optical depth correction M. Kim et al. 10.1016/j.rse.2013.12.003
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