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Dr. gen wang

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Proceedings Article | 24 May 2023 Paper

CO2 retrieval method based on GaoFen-5 satellite data

Yun Jiang, Xianhua Wang, Hanhan Ye, Hailiang Shi, Yue Pan, Gen Wang

Proceedings Volume 12706, 127060N (2023) https://doi.org/10.1117/12.2682540

KEYWORDS: Clouds, Carbon dioxide, Vegetation, Fluorescence, Chlorophyll, Satellites, MODIS, Scattering, Carbon monoxide, Tunable filters

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Cloud pollution problem in remote sensing data，Atmospheric scattering ,the presence and changes of chlorophyll fluorescence in vegetation, etc., all interfere with the inversion of CO₂, affecting the accuracy of CO₂ inversion.In this study, the Greenhouse Gases Monitoring Instrument (GMI) data collected from GaoFen-5 (GF-5) satellite was applied to the cloud detection study in O₂ A band. The detection results were compared with the cloud judgment product of the moderate resolution imaging spectroradiometer (MODIS), and the proposed algorithm can filterout 90% of the clear sky data. Based on this, a more in-depth study of atmospheric CO₂ retrieval was carried out. The CO₂ retrieval results were compared with those data collected from the Total Carbon Column Observing Network (TCCON) and Greenhouse Gases Observing Satellite, and the results showed that the average accuracy of CO₂ retrieval results was better than 1%. In addition, the correlation coefficient between the results of CO₂ retrieval method and the data collected from TCCON was 0.85. Due to the effect of vegetation chlorophyll fluorescence, the CO₂ retrieval results based on the GMI data were higher than TCCON collected data. After the corrections to reduce the effect of vegetation chlorophyll fluorescence, the correlation coefficient of the CO₂ retrieval results between GMI and TCCON

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