ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2018, Vol. 15, No. 7, pp. 9-14

Using a variational filtering algorithm to fill in surface temperature data gaps

V.S. Kochergin 1 , S.V. Kochergin 1 , S.V. Stanichny 1 
1 Marine Hydrophysical Institute RAS, Sevastopol, Russia
Accepted: 01.11.2018
DOI: 10.21046/2070-7401-2018-15-7-9-14
To restore the missing surface temperature measurement data, a filtration algorithm is considered. It is based on the variational approach, the search for the extremum of a quadratic functional, the representation of a function that approximates the measurement data as an expansion in terms of orthogonal functions. The procedure is based on a flat rotation of the original system by maximizing the quadratic functional characterizing the ratio of the coefficients of the system and its right-hand sides. In this case, a priori information is used about the possible maximum values of the decomposition coefficients. As a result of the algorithm, an equivalent system is obtained, in which the equations are arranged according to the rank of informativity. Approbation of the method on test examples and real data was carried out. As a source of data, a consistent long-term range of surface temperatures was taken for the same area in the Black Sea for thirty-five years. The measurement data were selected from the existing series randomly. The resulting gaps in the data had a duration from one to seven days. For two randomly selected years, experiments were conducted to restore the missing data. The procedure was implemented in two ways for the temperature values themselves and for deviations from the mean values. The surface temperature data were restored for the time points when the gaps in the measurement data were observed. As a result of numerical experiments, the effectiveness of the variational filtering algorithm is shown in the implementation of the procedure for recovering gaps in surface temperature measurement data.
Keywords: satellite data, surface temperature, variation algorithm
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