ИСТИНА

The key features of vegetation activity in arid wetlands are its high temporal dynamics, considerable spatial heterogeneity and extreme sensitivity to the environmental changes. These are the reasons why application of conventional techniques based on remote sensing data analysis to ecological monitoring of arid wetlands becomes challenging and can even produce misleading results. The lower Volga arid wetlands play very important role in local economy, being almost the only source of fresh water and the only region of naturally moistened soil to be used for agriculture and livestock among the surrounding desert and dry steppe. The vegetation activity proved to be the primary indicator of its state, that can be observed directly using satellite multispectral imagery. Because of the substantially big area of the region under study (over 9000 square kilometers), field observations cannot go on continuously all over its territory, and thus cannot provide certainly unbiased and representative results. The only source of information for balanced and broad view is remotely sensed data combined with meteorological, hydrological, geobotanical and other in-situ data. In this study we focus on indicators derived from the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) time series, a quantity that is recognized as one of Essential Climate Variables (ECV). It is developed for multiple satellite sensors and thus pretends to be universal for past and future global studies. Due to the above-mentioned exceptional features inherent to arid wetlands, FAPAR time series obtained from satellite imagery of a particular territory needs to be specially processed in order to produce more informative results. We intend to report a technique of constructing a time-continuous approximation of FAPAR time series along with several quantitative indicators for vegetation activity and its seasonal and annual dynamics. These indicators appear to reflect intrinsic properties of various plant communities of arid wetlands in lower Volga region, which cannot be derived from FAPAR time series directly. Our approach showed a great potential to be used in the analysis of ecosystem state. Examples of its application and comparison to the field data include plant cover classification, comprehensive ecosystem state estimation and quantitative mapping of key vegetation activity parameters for its monitoring. Once first published, the methodology undergoes continuous development and validation. New results on its application are going to be presented.