ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2019, Vol. 16, No. 6, pp. 143-154

Interpolation algorithm for the recovery of long satellite data time series of vegetation cover observation

T.S. Miklashevich 1 , S.А. Bartalev 1 , D.E. Plotnikov 1 
1 Space Research Institute RAS, Moscow, Russia
Accepted: 25.11.2019
DOI: 10.21046/2070-7401-2019-16-6-143-154
The importance of remote sensing methods based on time series analysis has increased in connection with the advent of the possibility of Earth surface regular satellite observation at high frequency. Analysis of Earth reflective characteristics dynamics is often used for land cover seasonal changes monitoring. Snow cover, atmospheric haze, clouds and shadows from clouds often impede continuous observation of vegetation. Image preprocessing allows filtering satellite observation data distorted due to adverse shooting conditions and hardware noise. This leads to time series gaps without, however, complete exclusion of distorted measurements. The paper presents an algorithm for recovery of long satellite data time series of vegetation cover observation, which is universal, with regard to the input data, in providing the possibility of restoring the information inaccessible for direct observation. Long time series allow continuous monitoring of the vegetation cover, both during vegetation and at rest in areas with unstable or short snow cover, including assessment of its long-term dynamics under the influence of various factors.
Keywords: remote sensing, time series, satellite data, vegetation indices, interpolation, data recovery, MODIS
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