Estimates of CO2 flux into the forest ecosystem based on the results of ground-based hyperspectral sounding of the atmosphere and an artificial neural network model
A.P. Rozanov1,2, I.V. Zadvornykh1, K.G. Gribanov1, V.I. Zakharov1,3
1Ural Federal University named after the first President of Russia B.N. Yeltsin, Ekaterinburg, Russia
2ITMO University, St. Petersburg, Russia
3N.N. Krasovskii Institute of Mathematics and Mechanics of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg, Russia
Keywords: atmosphere, carbon dioxide, hyperspectral sounding, artificial neural networks, MODIS
Abstract
The results of hyperspectral sounding of the atmosphere at the Ural Atmospheric Station in Kourovka from 2012-2022 are presented. It is shown that the average rate of CO2 growth in the atmosphere of this region is about 2.5 ppm per year. The amount of carbon dioxide absorbed from the atmosphere by the forest ecosystem per unit area during the growing season (April-September) in the vicinity of the carbon landfill in Kourovka is estimated using two independent methods. One method is based on the data on the CO2 total column obtained from sounding the atmosphere with a ground-based high-resolution infrared Fourier spectrometer. The second method is based on the use of an artificial neural network with data from spectral channels of the MODIS satellite sensor as injnit. The results obtained by both methods demonstrate good agreement. The estimates made show that the amount of CO2 absorbed from the atmosphere by the forest ecosystem in the vicinity of the carbon landfill site during the growing season of 2022 is about 1.5 t/ha (the first method) and about 1.3 t/ha (the second method).
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