Articles | Volume 9, issue 11
https://doi.org/10.5194/amt-9-5575-2016
© 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/amt-9-5575-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Improved MODIS Dark Target aerosol optical depth algorithm over land: angular effect correction
Yerong Wu
CORRESPONDING AUTHOR
Department of Geoscience and Remote Sensing (GRS), Delft University of
Technology (TUDelft), Stevinweg 1, 2628 CN Delft, the Netherlands
Martin de Graaf
Department of Geoscience and Remote Sensing (GRS), Delft University of
Technology (TUDelft), Stevinweg 1, 2628 CN Delft, the Netherlands
Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg
297, 3731 GA De Bilt, the Netherlands
Massimo Menenti
Department of Geoscience and Remote Sensing (GRS), Delft University of
Technology (TUDelft), Stevinweg 1, 2628 CN Delft, the Netherlands
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- Improving the accuracy of AOD by using multi-sensors data over the Red Sea and the Persian Gulf M. Pashayi et al. 10.1016/j.apr.2023.101948
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- Can explicit convection improve modelled dust in summertime West Africa? A. Roberts et al. 10.5194/acp-18-9025-2018
- Improvement of spatial-temporal resolution of aerosol profile by using multi-source satellite data over the Persian Gulf M. Pashayi et al. 10.1016/j.atmosenv.2022.119410
- A machine-learning-based cloud detection and thermodynamic-phase classification algorithm using passive spectral observations C. Wang et al. 10.5194/amt-13-2257-2020
- Assessment of aerosol burden over Ghana K. Fosu-Amankwah et al. 10.1016/j.sciaf.2021.e00971
- Particle Size Analysis of African Dust Haze over the Last 20 Years: A Focus on the Extreme Event of June 2020 L. Euphrasie-Clotilde et al. 10.3390/atmos12040502
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- A minimum albedo aerosol retrieval method for the new-generation geostationary meteorological satellite Himawari-8 X. Yan et al. 10.1016/j.atmosres.2018.02.021
- Influence of industrial sustainability transition on air quality in a typical resource-exhausted city J. Wang & X. Li 10.1016/j.heliyon.2024.e25138
- Evaluation and comparison of MODIS and MISR aerosol products with ground-based monitoring stations in the Amazon Basin V. Schumacher et al. 10.1016/j.atmosenv.2024.120597
- The Response of the Aerosol Distribution to Monsoon Intensity Over the Summer Monsoon Transition Zone B. Bai et al. 10.3389/feart.2019.00356
- SAHARA: A Simplified AtmospHeric Correction AlgoRithm for Chinese gAofen Data: 1. Aerosol Algorithm L. She et al. 10.3390/rs9030253
- High-resolution spatiotemporal mapping of PM2.5 concentrations at Mainland China using a combined BME-GWR technique L. Xiao et al. 10.1016/j.atmosenv.2017.10.062
1 citations as recorded by crossref.
Latest update: 13 Nov 2024
Short summary
In this paper, we developed a new algorithm to improve the retrieval of aerosol optical depth (AOD) over land with satellite measurement by refining the shape of the spectral surface reflectance to improve the estimated background reflectance in the channel used for AOD retrieval. The results show that the angular effects of the retrievals are largely reduced, including fewer occurrences of negative retrievals. This implies that the users can get more accurate data without angular bias.
In this paper, we developed a new algorithm to improve the retrieval of aerosol optical depth...