NON-LINEAR TRENDS OF PLANTS NET PRIMARY PRODUCTION IN SOUTH OF KRASNOYARSK KRAI WITH SATELLITE DATA: METHODS AND APPROACHES
This is a study of the spatial distribution of non-linear trend of net primary production (NPP) of vegetation obtained by different methods based on remote sensing. The study was conducted in the south of the Krasnoyarsk Territory, has a large variety of natural landscapes from the steppes to the high alpine meadows of the Sayan Mountains. We used methods of STL (Seasonal-Trend Decomposition Procedure Based on Loess) and ССА (Singular Spectrum Analysis). Comparison of the results obtained by these methods has shown that the decomposition of time series of remote sensing data and further analysis of the trends is more suitable method of STL. This method has a flexible configuration and can detect short-term cycles. ССА method is not suitable for studying trends in short time series, but may be used for prediction.