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A constructive review of the State Forest Inventory in the Russian FederationAuthor(s): Alexander Alekseev; Erkki Tomppo; Ronald E. McRoberts; Klaus von Gadow
Source: Forest Ecosystems
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
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DescriptionThe State Forest Inventory (SFI) in the Russian Federation is a relatively new project that is little known in the English-language scientific literature. Following the stipulations of the Forest Act of 2006, the first SFI sample plots in this vast territory were established in 2007. The 34 Russian forest regions were the basic geographical units for all statistical estimates and served as a first-level stratification, while a second level was based on old inventory data and remotely sensed data. The sampling design was to consist of a simple random sample of 84,700 circular 500 m2 sample plots over forest land. Each sample plot consists of three nested concentric circular subplots with radii of 12.62, 5.64 and 2.82m and additional subplots for assessing and describing undergrowth, regeneration and ground vegetation. In total, 117 variables were to be measured or assessed on each plot. Although field work has begun, the methodology has elicited some criticism. The simple random sampling design is less efficient than a systematic design featuring sample plot clusters and a mix of temporary and permanent plots. The second-level stratification is mostly ineffective for increasing precision. Qualitative variables, which are not always essential, are dominant, while important quantitative variables are under-represented. Because of very slow progress, in 2018 the original plan was adjusted by reducing the number of permanent sample plots from 84,700 to 68,287 so that the first SFI cycle could be completed by 2020.
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CitationAlekseev, Alexander; Tomppo, Erkki; McRoberts, Ronald E.; von Gadow, Klaus. 2019. A constructive review of the State Forest Inventory in the Russian Federation. Forest Ecosystems. 6(1): 102-. https://doi.org/10.1186/s40663-019-0165-3.
KeywordsForest inventory, Sampling design, Stratification, Remote sensing, Bias, Accuracy
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