The complete data fusion method, generalized to the case of fusing profiles of atmospheric variables retrieved on different vertical grids and referred to different true values, is applied to ozone profiles retrieved from simulated measurements in the ultraviolet, visible, and thermal infrared spectral ranges for the Sentinel-4 and Sentinel-5 missions of the Copernicus program. In this study, the production and characterization of combined low Earth orbit (Sentinel-5) and geostationary Earth orbit (Sentinel-4) fused ozone data is performed. Fused and standard products have been compared and a performance assessment of the generalized complete data fusion is presented. The analysis of the output products of the complete data fusion algorithm and of the standard processing using quality quantifiers demonstrates that the generalized complete data fusion algorithm provides products of better quality when compared with standard products.

Data Fusion Analysis of Sentinel-4 and Sentinel-5 Simulated Ozone Data

Cecilia Tirelli;Simone Ceccherini;Nicola Zoppetti;Samuele Del Bianco;Marco Gai;Flavio Barbara;Ugo Cortesi
2020

Abstract

The complete data fusion method, generalized to the case of fusing profiles of atmospheric variables retrieved on different vertical grids and referred to different true values, is applied to ozone profiles retrieved from simulated measurements in the ultraviolet, visible, and thermal infrared spectral ranges for the Sentinel-4 and Sentinel-5 missions of the Copernicus program. In this study, the production and characterization of combined low Earth orbit (Sentinel-5) and geostationary Earth orbit (Sentinel-4) fused ozone data is performed. Fused and standard products have been compared and a performance assessment of the generalized complete data fusion is presented. The analysis of the output products of the complete data fusion algorithm and of the standard processing using quality quantifiers demonstrates that the generalized complete data fusion algorithm provides products of better quality when compared with standard products.
2020
Istituto di Fisica Applicata - IFAC
Ozone; Algorithms; Data processing; Remote sensing; Satellite observations; Inverse methods
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/367605
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