Highlights: What are the main findings? Calculate dense maps of Aerosol Optical Depth (AOD) from Sentinel-2/3 images. Discriminate the type of AOD, either coarse or fine, from its scattering properties. What are the implication of the main findings? The maps produced from S2 and S3 data are merged to achieve a spatio-temporal fusion. The method does not require the availability of ground-based auxiliary data. In this study, the authors wish to introduce an unsupervised procedure designed for real-time generation of maps depicting advected aerosols, specifically focusing on desert dust and smoke originating from biomass combustion. This innovative approach leverages the high-resolution capabilities provided by Sentinel-2 imagery, operating at a 10 m scale, which is particularly advantageous for urban settings. Concurrently, it takes advantage of the near-daily revisit frequency afforded by Sentinel-3. The methodology involves generating aerosol maps at a 10 m resolution using bands 2, 3, 4, and 5 of Sentinel-2, available in L1C and L2A formats, conducted every five days, contingent upon the absence of cloud cover. Subsequently, this map is enhanced every two days through spatial modulation, utilizing a similar map derived from the visible and near-infrared observations (VNIR) captured by the OLCI instrument aboard Sentinel-3, which is accessible at a 300 m scale. Data from the two satellites undergo independent processing, with integration at the feature level. This process combines Sentinel-3 and Sentinel-2 maps to update aerosol concentrations in each 300 m × 300 m grid every two days or more frequently. For the dates when Sentinel-2 data is unavailable, the spatial texture or the aerosol distribution within these grid cells is extrapolated. This spatial index represents an advancement over prior studies that focused on differentiating between dust and smoke based on their scattering and absorption characteristics. The entire process is rigorously validated by comparing it with point measurements of fine- and coarse-mode Aerosol Optical Depth (AOD) obtained from AERONET stations situated at the test sites, ensuring the reliability and accuracy of the generated maps.

Fusion of Sentinel-2 and Sentinel-3 Images for Producing Daily Maps of Advected Aerosols at Urban Scale / Alparone L.; Bianchini M.; Garzelli A.; Lolli S.. - In: REMOTE SENSING. - ISSN 2072-4292. - ELETTRONICO. - 18:(2026), pp. 116.0-116.0. [10.3390/rs18010116]

Fusion of Sentinel-2 and Sentinel-3 Images for Producing Daily Maps of Advected Aerosols at Urban Scale

Alparone L.
;
2026

Abstract

Highlights: What are the main findings? Calculate dense maps of Aerosol Optical Depth (AOD) from Sentinel-2/3 images. Discriminate the type of AOD, either coarse or fine, from its scattering properties. What are the implication of the main findings? The maps produced from S2 and S3 data are merged to achieve a spatio-temporal fusion. The method does not require the availability of ground-based auxiliary data. In this study, the authors wish to introduce an unsupervised procedure designed for real-time generation of maps depicting advected aerosols, specifically focusing on desert dust and smoke originating from biomass combustion. This innovative approach leverages the high-resolution capabilities provided by Sentinel-2 imagery, operating at a 10 m scale, which is particularly advantageous for urban settings. Concurrently, it takes advantage of the near-daily revisit frequency afforded by Sentinel-3. The methodology involves generating aerosol maps at a 10 m resolution using bands 2, 3, 4, and 5 of Sentinel-2, available in L1C and L2A formats, conducted every five days, contingent upon the absence of cloud cover. Subsequently, this map is enhanced every two days through spatial modulation, utilizing a similar map derived from the visible and near-infrared observations (VNIR) captured by the OLCI instrument aboard Sentinel-3, which is accessible at a 300 m scale. Data from the two satellites undergo independent processing, with integration at the feature level. This process combines Sentinel-3 and Sentinel-2 maps to update aerosol concentrations in each 300 m × 300 m grid every two days or more frequently. For the dates when Sentinel-2 data is unavailable, the spatial texture or the aerosol distribution within these grid cells is extrapolated. This spatial index represents an advancement over prior studies that focused on differentiating between dust and smoke based on their scattering and absorption characteristics. The entire process is rigorously validated by comparing it with point measurements of fine- and coarse-mode Aerosol Optical Depth (AOD) obtained from AERONET stations situated at the test sites, ensuring the reliability and accuracy of the generated maps.
2026
18
0
0
Alparone L.; Bianchini M.; Garzelli A.; Lolli S.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1450698
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