Articles | Volume 12, issue 19
https://doi.org/10.5194/acp-12-9167-2012
© Author(s) 2012. 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-12-9167-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
10 Oct 2012
Research article |
| 10 Oct 2012
Retrieval of aerosol optical depth over land based on a time series technique using MSG/SEVIRI data
L. Mei
State Key Laboratory of Remote Sensing Science, jointly sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing
University of the Chinese Academy of Sciences, Beijing 100049, China
Y. Xue
State Key Laboratory of Remote Sensing Science, jointly sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing
Faculty of Computing, London Metropolitan University, 166-220 Holloway Road, London N7 8DB, UK
G. de Leeuw
Department of Physics, University of Helsinki, Helsinki, Finland
Finnish Meteorological Institute, Climate Change Unit, Helsinki, Finland
Netherlands Organisation for Applied Scientific Research TNO, Utrecht, The Netherlands
T. Holzer-Popp
German Remote Sensing Data Center, German Aerospace Center, Oberpfaffenhofen, 82234 Wessling, Germany
J. Guang
State Key Laboratory of Remote Sensing Science, jointly sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing
Y. Li
State Key Laboratory of Remote Sensing Science, jointly sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing
University of the Chinese Academy of Sciences, Beijing 100049, China
L. Yang
School of Geography, Beijing Normal University, Beijing, China
H. Xu
State Key Laboratory of Remote Sensing Science, jointly sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing
University of the Chinese Academy of Sciences, Beijing 100049, China
X. Xu
Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, No.9 Dengzhuang South Road, Haidian District, Beijing 100094, China
University of the Chinese Academy of Sciences, Beijing 100049, China
C. Li
Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, No.9 Dengzhuang South Road, Haidian District, Beijing 100094, China
University of the Chinese Academy of Sciences, Beijing 100049, China
Y. Wang
State Key Laboratory of Remote Sensing Science, jointly sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing
University of the Chinese Academy of Sciences, Beijing 100049, China
C. Wu
State Key Laboratory of Remote Sensing Science, jointly sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing
T. Hou
Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, No.9 Dengzhuang South Road, Haidian District, Beijing 100094, China
University of the Chinese Academy of Sciences, Beijing 100049, China
X. He
State Key Laboratory of Remote Sensing Science, jointly sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing
University of the Chinese Academy of Sciences, Beijing 100049, China
J. Liu
State Key Laboratory of Remote Sensing Science, jointly sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing
University of the Chinese Academy of Sciences, Beijing 100049, China
J. Dong
State Key Laboratory of Remote Sensing Science, jointly sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing
University of the Chinese Academy of Sciences, Beijing 100049, China
Z. Chen
Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, No.9 Dengzhuang South Road, Haidian District, Beijing 100094, China
University of the Chinese Academy of Sciences, Beijing 100049, China
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Cited
33 citations as recorded by crossref.
- Dust Detection and Intensity Estimation Using Himawari-8/AHI Observation L. She et al. 10.3390/rs10040490
- Aerosol optical depth retrieval over snow using AATSR data L. Mei et al. 10.1080/01431161.2013.786197
- Synergistic Retrieval of Multitemporal Aerosol Optical Depth Over North China Plain Using Geostationary Satellite Data of Himawari‐8 S. Shi et al. 10.1029/2017JD027963
- A Dual-Channel Aerosol Optical Depth Retrieval Algorithm Incorporating the BRDF Effect from AVHRR over Eastern Asia Y. Wang et al. 10.3390/rs13030365
- SEVIRI Aerosol Optical Depth Validation Using AERONET and Intercomparison with MODIS in Central and Eastern Europe N. Ajtai et al. 10.3390/rs13050844
- New insights into the vertical structure of the September 2015 dust storm employing eight ceilometers and auxiliary measurements over Israel L. Uzan et al. 10.5194/acp-18-3203-2018
- Retrieval and application of leaf area index over China using HJ-1 data X. Zhao et al. 10.1080/19475705.2016.1238854
- Near-Real-Time Application of SEVIRI Aerosol Optical Depth Algorithm O. Zawadzka-Manko et al. 10.3390/rs12091481
- Mapping Surface Broadband Albedo from Satellite Observations: A Review of Literatures on Algorithms and Products Y. Qu et al. 10.3390/rs70100990
- 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
- Effect of Heat Wave Conditions on Aerosol Optical Properties Derived from Satellite and Ground-Based Remote Sensing over Poland I. Stachlewska et al. 10.3390/rs9111199
- 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
- Developing Land Surface Directional Reflectance and Albedo Products from Geostationary GOES-R and Himawari Data: Theoretical Basis, Operational Implementation, and Validation T. He et al. 10.3390/rs11222655
- Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China D. Li et al. 10.3390/rs12060978
- SAHARA: A Simplified AtmospHeric Correction AlgoRithm for Chinese gAofen Data: 1. Aerosol Algorithm L. She et al. 10.3390/rs9030253
- A Hybrid Algorithm for Dust Aerosol Detection: Integrating Forward Radiative Transfer Simulations and Machine Learning J. Jin et al. 10.1109/TGRS.2023.3301061
- A study of the impact of spatial resolution on the estimation of particle matter concentration from the aerosol optical depth retrieved from satellite observations L. Mei et al. 10.1080/01431161.2019.1601279
- Retrieval of aerosol optical depth over land surfaces from AVHRR data L. Mei et al. 10.5194/amt-7-2411-2014
- SAMIRA-SAtellite Based Monitoring Initiative for Regional Air Quality K. Stebel et al. 10.3390/rs13112219
- Retrieval of hourly aerosol single scattering albedo over land using geostationary satellite data X. Jiang et al. 10.1038/s41612-024-00690-6
- Aerosol remote sensing in polar regions C. Tomasi et al. 10.1016/j.earscirev.2014.11.001
- 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
- Exploring the effects of landscape structure on aerosol optical depth (AOD) patterns using GIS and HJ-1B images L. Ye et al. 10.1039/C5EM00538H
- A Critical Evaluation of Deep Blue Algorithm Derived AVHRR Aerosol Product Over China L. Mei et al. 10.1029/2018JD029929
- 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
- Retrieval of Aerosol Optical Depth from Optimal Interpolation Approach Applied to SEVIRI Data O. Zawadzka & K. Markowicz 10.3390/rs6087182
- Remote sensing of atmospheric aerosol using spaceborne optical observations A. Kokhanovsky 10.1016/j.earscirev.2012.10.008
- Monitoring aerosols over Europe: an assessment of the potential benefit of assimilating the VIS04 measurements from the future MTG/FCI geostationary imager M. Descheemaecker et al. 10.5194/amt-12-1251-2019
- 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
- Air Quality over China G. de Leeuw et al. 10.3390/rs13173542
- Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations A. Di et al. 10.3390/rs8090702
- Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization C. Jin et al. 10.3390/rs13224689
- Consistent retrieval of multiple parameters from GOES-R top of atmosphere reflectance data H. Xiong et al. 10.1080/01431161.2020.1766151
32 citations as recorded by crossref.
- Dust Detection and Intensity Estimation Using Himawari-8/AHI Observation L. She et al. 10.3390/rs10040490
- Aerosol optical depth retrieval over snow using AATSR data L. Mei et al. 10.1080/01431161.2013.786197
- Synergistic Retrieval of Multitemporal Aerosol Optical Depth Over North China Plain Using Geostationary Satellite Data of Himawari‐8 S. Shi et al. 10.1029/2017JD027963
- A Dual-Channel Aerosol Optical Depth Retrieval Algorithm Incorporating the BRDF Effect from AVHRR over Eastern Asia Y. Wang et al. 10.3390/rs13030365
- SEVIRI Aerosol Optical Depth Validation Using AERONET and Intercomparison with MODIS in Central and Eastern Europe N. Ajtai et al. 10.3390/rs13050844
- New insights into the vertical structure of the September 2015 dust storm employing eight ceilometers and auxiliary measurements over Israel L. Uzan et al. 10.5194/acp-18-3203-2018
- Retrieval and application of leaf area index over China using HJ-1 data X. Zhao et al. 10.1080/19475705.2016.1238854
- Near-Real-Time Application of SEVIRI Aerosol Optical Depth Algorithm O. Zawadzka-Manko et al. 10.3390/rs12091481
- Mapping Surface Broadband Albedo from Satellite Observations: A Review of Literatures on Algorithms and Products Y. Qu et al. 10.3390/rs70100990
- 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
- Effect of Heat Wave Conditions on Aerosol Optical Properties Derived from Satellite and Ground-Based Remote Sensing over Poland I. Stachlewska et al. 10.3390/rs9111199
- 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
- Developing Land Surface Directional Reflectance and Albedo Products from Geostationary GOES-R and Himawari Data: Theoretical Basis, Operational Implementation, and Validation T. He et al. 10.3390/rs11222655
- Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China D. Li et al. 10.3390/rs12060978
- SAHARA: A Simplified AtmospHeric Correction AlgoRithm for Chinese gAofen Data: 1. Aerosol Algorithm L. She et al. 10.3390/rs9030253
- A Hybrid Algorithm for Dust Aerosol Detection: Integrating Forward Radiative Transfer Simulations and Machine Learning J. Jin et al. 10.1109/TGRS.2023.3301061
- A study of the impact of spatial resolution on the estimation of particle matter concentration from the aerosol optical depth retrieved from satellite observations L. Mei et al. 10.1080/01431161.2019.1601279
- Retrieval of aerosol optical depth over land surfaces from AVHRR data L. Mei et al. 10.5194/amt-7-2411-2014
- SAMIRA-SAtellite Based Monitoring Initiative for Regional Air Quality K. Stebel et al. 10.3390/rs13112219
- Retrieval of hourly aerosol single scattering albedo over land using geostationary satellite data X. Jiang et al. 10.1038/s41612-024-00690-6
- Aerosol remote sensing in polar regions C. Tomasi et al. 10.1016/j.earscirev.2014.11.001
- 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
- Exploring the effects of landscape structure on aerosol optical depth (AOD) patterns using GIS and HJ-1B images L. Ye et al. 10.1039/C5EM00538H
- A Critical Evaluation of Deep Blue Algorithm Derived AVHRR Aerosol Product Over China L. Mei et al. 10.1029/2018JD029929
- 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
- Retrieval of Aerosol Optical Depth from Optimal Interpolation Approach Applied to SEVIRI Data O. Zawadzka & K. Markowicz 10.3390/rs6087182
- Remote sensing of atmospheric aerosol using spaceborne optical observations A. Kokhanovsky 10.1016/j.earscirev.2012.10.008
- Monitoring aerosols over Europe: an assessment of the potential benefit of assimilating the VIS04 measurements from the future MTG/FCI geostationary imager M. Descheemaecker et al. 10.5194/amt-12-1251-2019
- 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
- Air Quality over China G. de Leeuw et al. 10.3390/rs13173542
- Dust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations A. Di et al. 10.3390/rs8090702
- Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization C. Jin et al. 10.3390/rs13224689
1 citations as recorded by crossref.
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