Natural and anthropogenic aerosol emissions play a fundamental role both modulating directly the incoming solar radiation and affecting the air quality. Likewise, their indirect effects impact cloud lifetime, atmospheric column thermodynamics and precipitation patterns. For this reason, it is of crucial importance to assess aerosol spatial and temporal variability to reduce the uncertainty in forecasting future scenarios by the climatological models. In this study we developed an image based robust methodology that permits to retrieve the atmospheric path radiance and then the Aerosol Optical Depth (AOD) using the different bands satellite high-resolution spatial images, e.g., Landsat, Sentinel, QuickBird and Ikonos, and a radiative transfer model. The validity and the limits of the proposed methodology are investigated through ground based lidar and sunphotometer observations obtained from the European Aerosol Lidar Network (EARLINET), the NASA MicroPulse Lidar Network (MPLNET) and the NASA AERONET network respectively.
High-Resolution Satellite Image Based Aerosol Optical Depth Retrieval Method: Validation Through EARLINET and NASA MPLNET Lidar Measurements and NASA AERONET Sunphotometer Data / Lolli S.; Vivone G.; Alparone L.; Garzelli A.; Bilal M.; Cimini D.; Campbell J.R.; Welton E.J.; Pappalardo G.. - ELETTRONICO. - 2019-:(2019), pp. 3943-3947. (Intervento presentato al convegno 2019 PhotonIcs and Electromagnetics Research Symposium - Spring, PIERS-Spring 2019 tenutosi a Rome; Italy nel 17 June 2019 through 20 June 2019) [10.1109/PIERS-Spring46901.2019.9017776].
High-Resolution Satellite Image Based Aerosol Optical Depth Retrieval Method: Validation Through EARLINET and NASA MPLNET Lidar Measurements and NASA AERONET Sunphotometer Data
Alparone L.;
2019
Abstract
Natural and anthropogenic aerosol emissions play a fundamental role both modulating directly the incoming solar radiation and affecting the air quality. Likewise, their indirect effects impact cloud lifetime, atmospheric column thermodynamics and precipitation patterns. For this reason, it is of crucial importance to assess aerosol spatial and temporal variability to reduce the uncertainty in forecasting future scenarios by the climatological models. In this study we developed an image based robust methodology that permits to retrieve the atmospheric path radiance and then the Aerosol Optical Depth (AOD) using the different bands satellite high-resolution spatial images, e.g., Landsat, Sentinel, QuickBird and Ikonos, and a radiative transfer model. The validity and the limits of the proposed methodology are investigated through ground based lidar and sunphotometer observations obtained from the European Aerosol Lidar Network (EARLINET), the NASA MicroPulse Lidar Network (MPLNET) and the NASA AERONET network respectively.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.