Determination of the stand stock using ALOS Palsar satellite data: the case of Toratau Geopark

   Recently, remote methods for analyzing the dynamics and condition of a stand have become widely used. In order to meet the criteria of the UNESCO Global Geopark, it is important for Toratau Geopark to conduct research on global climate change and sustainable management of natural resources. Using vector data from the 2017 forest management and statistical data from the AlOS Palsar raster, a regression and correlation analysis was performed. Raster statistics are obtained using the SAGA GIS module (QGIS program) tool – raster statistics into polygons (average value). Also, based on the obtained regression equation, images reflecting the stock of the stand of the Toratau Geopark for 2017 and 2023 were constructed. The regression analysis showed the presence of a significant relationship between the values of AlOS Palsar pixels and stand stocks – Pearson correlation coefficient r = 0.62, coefficient of determination R² = 0.38. The results of the 2017 stand stock assessment according to the tax descriptions and ALOS Palsar (HV polarization) differ slightly. The distribution of the maximum values of the stand stock according to ALOS Palsar data also corresponds to the northern part of the geopark, but the number of polygons with the maximum value is lower than according to the taxation data. The maximum value range is 279-497 m³ per ha. in the image of 2023, areas with a negative stock of stand are marked – they correspond to the cut-down sites. The proposed approach can be used to monitor logging, the phytosanitary condition of the stand and the impact of recreation on the forests of Toratau Geopark.

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