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Mass forest survey and state forest inventory data: specification of the discrepancies, causes, analysis  [2014]

Farber, S.K., Russian Academy of Sciences. Siberian Branch, Krasnoyarsk (Russian Federation). The V.N. Sukachiev Inst. of Forest Science Bryukhanov, N.V.

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State forest inventory (SFI) is the forest inventory operation that was not performed in Russia before. Its purpose is to identify the total forest area characteristics including wood volume in Russian regions. There are several papers about the existence of huge differences between the forest management and SFI data. The reasons for differences in land category and forest formation on sample slots (SS) and forest compartments (FC) were found on the basis of two forest ranger stations in Krasnoyarsk Angara river region. The amount of sample items was 340. The SS and FC were compared in order to identify the characteristics of differences between SFI data and forest management materials; visual analysis of SS and FC dispatching on plans of forest stands and relief maps was performed in order to identify the potential differences. Reconciliation of SS of SFI data and FC showed significant mistakes due to inhomogeneous structure of FC and some forest management decisions in third category. However, they do not influence the data differences. Systematic errors occur because of SFI methodology peculiarities, and are the main reason for differences between traditional forest management and SFI data. These errors can be solved. To achieve this it is necessary to refuse from stratification of total forest area characteristics at the planning stage of choosing the SS. The relief and soil hydrological characteristics should be taken into consideration in a stratific
ation analysis. SS location choice based on the landscape peculiarities, far from the pathway, will allow to eliminate the systematic errors. SFI and traditional forest management will be considered as no concurenting, but supplementing each other matters.

From the journal

Siberian Journal of Forest Science

ISSN : 2311-1410