Articles | Volume 7, issue 9
https://doi.org/10.5194/amt-7-3151-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-7-3151-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
26 Sep 2014
Research article |
| 26 Sep 2014
Satellite retrieval of aerosol microphysical and optical parameters using neural networks: a new methodology applied to the Sahara desert dust peak
M. Taylor
Institute for Environmental Research and Sustainable Development (IERSD), National Observatory of Athens (NOA), Metaxa & Vas. Pavlou, Penteli, 15236, Athens, Greece
S. Kazadzis
Institute for Environmental Research and Sustainable Development (IERSD), National Observatory of Athens (NOA), Metaxa & Vas. Pavlou, Penteli, 15236, Athens, Greece
A. Tsekeri
Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing (IAASARS), National Observatory of Athens (NOA), Metaxa & Vas. Pavlou, Penteli, 15236, Athens, Greece
A. Gkikas
Laboratory of Meteorology, Physics Department, University of Ioannina, Greece
V. Amiridis
Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing (IAASARS), National Observatory of Athens (NOA), Metaxa & Vas. Pavlou, Penteli, 15236, Athens, Greece
Viewed
Total article views: 5,709 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 17 Dec 2013)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,187 | 2,186 | 336 | 5,709 | 207 | 219 |
- HTML: 3,187
- PDF: 2,186
- XML: 336
- Total: 5,709
- BibTeX: 207
- EndNote: 219
Total article views: 4,066 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 26 Sep 2014)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,325 | 1,464 | 277 | 4,066 | 178 | 205 |
- HTML: 2,325
- PDF: 1,464
- XML: 277
- Total: 4,066
- BibTeX: 178
- EndNote: 205
Total article views: 1,643 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 17 Dec 2013)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 862 | 722 | 59 | 1,643 | 29 | 14 |
- HTML: 862
- PDF: 722
- XML: 59
- Total: 1,643
- BibTeX: 29
- EndNote: 14
Cited
22 citations as recorded by crossref.
- Deep learning in environmental remote sensing: Achievements and challenges Q. Yuan et al.
- A neural network aerosol-typing algorithm based on lidar data D. Nicolae et al.
- TEMIS UV product validation using NILU-UV ground-based measurements in Thessaloniki, Greece M. Zempila et al.
- A physical knowledge-based machine learning method for near-real-time dust aerosol properties retrieval from the Himawari-8 satellite data J. Li et al.
- Utilizing deep learning techniques in operational system of geo-KOMPSAT-2A satellite for estimating solar radiation and aerosol optical depth J. Ha et al.
- Analysis of aerosol absorption properties and transport over North Africa and the Middle East using AERONET data A. Farahat et al.
- Earth-Observation-Based Estimation and Forecasting of Particulate Matter Impact on Solar Energy in Egypt P. Kosmopoulos et al.
- A Decadal Data Set of Global Atmospheric Dust Retrieved From IASI Satellite Measurements L. Clarisse et al.
- Modeling the relationship between photosynthetically active radiation and global horizontal irradiance using singular spectrum analysis M. Zempila et al.
- The retrieval of aerosol optical properties based on a random forest machine learning approach: Exploration of geostationary satellite images F. Bao et al.
- Neural network radiative transfer solvers for the generation of high resolution solar irradiance spectra parameterized by cloud and aerosol parameters M. Taylor et al.
- Retrieval of aerosol optical depth from surface solar radiation measurements using machine learning algorithms, non-linear regression and a radiative transfer-based look-up table J. Huttunen et al.
- Time series retrieval of Multi-wavelength Aerosol optical depth by adapting Transformer (TMAT) using Himawari-8 AHI data L. She et al.
- Forest Fire Smoke Detection Using Back-Propagation Neural Network Based on MODIS Data X. Li et al.
- NILU-UV multi-filter radiometer total ozone columns: Comparison with satellite observations over Thessaloniki, Greece M. Zempila et al.
- A method for land surface temperature retrieval based on model-data-knowledge-driven and deep learning H. Wang et al.
- Combined neural network/Phillips–Tikhonov approach to aerosol retrievals over land from the NASA Research Scanning Polarimeter A. Di Noia et al.
- Assessment of surface solar irradiance derived from real-time modelling techniques and verification with ground-based measurements P. Kosmopoulos et al.
- Validation of OMI erythemal doses with multi-sensor ground-based measurements in Thessaloniki, Greece M. Zempila et al.
- Wide and Deep Learning Model for Satellite-Based Real-Time Aerosol Retrievals in China N. Luo et al.
- An ensemble machine learning method to retrieve aerosol parameters from ground-based Sun-sky photometer measurements Q. Li et al.
- Air pollution in the Arabian Peninsula (Saudi Arabia, the United Arab Emirates, Kuwait, Qatar, Bahrain, and Oman): causes, effects, and aerosol categorization A. Farahat
22 citations as recorded by crossref.
- Deep learning in environmental remote sensing: Achievements and challenges Q. Yuan et al.
- A neural network aerosol-typing algorithm based on lidar data D. Nicolae et al.
- TEMIS UV product validation using NILU-UV ground-based measurements in Thessaloniki, Greece M. Zempila et al.
- A physical knowledge-based machine learning method for near-real-time dust aerosol properties retrieval from the Himawari-8 satellite data J. Li et al.
- Utilizing deep learning techniques in operational system of geo-KOMPSAT-2A satellite for estimating solar radiation and aerosol optical depth J. Ha et al.
- Analysis of aerosol absorption properties and transport over North Africa and the Middle East using AERONET data A. Farahat et al.
- Earth-Observation-Based Estimation and Forecasting of Particulate Matter Impact on Solar Energy in Egypt P. Kosmopoulos et al.
- A Decadal Data Set of Global Atmospheric Dust Retrieved From IASI Satellite Measurements L. Clarisse et al.
- Modeling the relationship between photosynthetically active radiation and global horizontal irradiance using singular spectrum analysis M. Zempila et al.
- The retrieval of aerosol optical properties based on a random forest machine learning approach: Exploration of geostationary satellite images F. Bao et al.
- Neural network radiative transfer solvers for the generation of high resolution solar irradiance spectra parameterized by cloud and aerosol parameters M. Taylor et al.
- Retrieval of aerosol optical depth from surface solar radiation measurements using machine learning algorithms, non-linear regression and a radiative transfer-based look-up table J. Huttunen et al.
- Time series retrieval of Multi-wavelength Aerosol optical depth by adapting Transformer (TMAT) using Himawari-8 AHI data L. She et al.
- Forest Fire Smoke Detection Using Back-Propagation Neural Network Based on MODIS Data X. Li et al.
- NILU-UV multi-filter radiometer total ozone columns: Comparison with satellite observations over Thessaloniki, Greece M. Zempila et al.
- A method for land surface temperature retrieval based on model-data-knowledge-driven and deep learning H. Wang et al.
- Combined neural network/Phillips–Tikhonov approach to aerosol retrievals over land from the NASA Research Scanning Polarimeter A. Di Noia et al.
- Assessment of surface solar irradiance derived from real-time modelling techniques and verification with ground-based measurements P. Kosmopoulos et al.
- Validation of OMI erythemal doses with multi-sensor ground-based measurements in Thessaloniki, Greece M. Zempila et al.
- Wide and Deep Learning Model for Satellite-Based Real-Time Aerosol Retrievals in China N. Luo et al.
- An ensemble machine learning method to retrieve aerosol parameters from ground-based Sun-sky photometer measurements Q. Li et al.
- Air pollution in the Arabian Peninsula (Saudi Arabia, the United Arab Emirates, Kuwait, Qatar, Bahrain, and Oman): causes, effects, and aerosol categorization A. Farahat
Saved (final revised paper)
Latest update: 24 May 2026
