Neural network temperature and moisture retrieval technique for real-time processing of FengYun-4B/GIIRS hyperspectral radiances
Author:
Funder
National Key Research and Development Program of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00703-024-01037-9.pdf
Reference28 articles.
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2. Bai W, Zhang P, Liu H, Zhang W, Qi C, Ma G, Li G (2023) A fast piecewise-defined neural network method to retrieve temperature and humidity profile for the vertical atmospheric sounding system of FengYun-3E satellite. IEEE Trans Geosci Remote Sens 61:3247776. https://doi.org/10.1109/TGRS.2023.3247776
3. Bouillon M, Safieddine S, Hadji-Lazaro J et al (2020) Ten-year assessment of IASI radiance and temperature. Remote Sens 12(15):2393. https://doi.org/10.3390/rs12152393
4. Cai X, Bao Y, Petropoulos GP et al (2020) Temperature and humidity profile retrieval from FY4-GIIRS hyperspectral data using artificial neural networks. Remote Sens 12(11):1872. https://doi.org/10.3390/rs12111872
5. Chahine MT, Pagano TS, Aumann HH et al (2006) AIRS: improving weather forecasting and providing new data on greenhouse gases. Bull Am Meterol Soc 87(7):911–926. https://doi.org/10.1175/BAMS-87-7-911
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