Modeling of the taxation characteristics of tree stands in the Arctic land area using allometric equations and remote sensing data

The research is aimed at developing an integrated approach to assessing the taxation characteristics (stock, average diameter and height) of tundra stands in the Arctic land area. The methodology is based on the integration of data from the State Forest Inventory (SFI) for 2021 with high-resolution aerial photography in 2022. The paper adapts the classical allometric models of Woda, Reinecke and Hilmi for the conditions of tundra forests and rare-coniferous taiga for Siberian spruce stands (Picea obovata L.) of the V class of bonity. The exponent in the equations is fixed at the theoretical level of -0.5, which made it possible to calculate the regional constants of the models. To determine the key parameter of the models, the density of the stand, aerial photographs were decoded using stereoscopic analysis in the PHOTOMOD program. Adapted parameters of the equations wereobtained: for the stand stock (C₁=3279.63, R2=0.816), the average diameter (c₃=404.76, R2=0.703) and the average height (c₂=298.47, R2=0.550). Testing of the Uoda model at control sites revealed a systematic discrepancy with the SFI data, which is explained by the need to accurately account for the relative density of stands when switching from remote sensing data to taxation parameters. The practical significance of the work lies in the creation of a methodological framework for remote inventory of forest resources in hard-to-reach Arctic territories, which makes it possible to reduce the amount of expensive ground work.