Modeling of the relationshi̇ps between aboveground biomass and leaf area index in pure red pine stands (a case study in Sariyayla forest planning unit)

This study was conducted in pure red pine (Pinus brutia Ten.) stands within the boundaries of Mersin Regional Directorate of Forestry, Anamur Forest Enterprise, Sarıyayla Forest Planning Unit. A total of 257 sample plot data were utilized in the study. Using the sample field data, each sample plot's aboveground biomass (AGB) value was calculated using the single-entry equation developed by Şahin (2015) for pure red pine stands. In addition, leaf area index (LAI) images were produced for each month using Sentinel-2 satellite images (except January). Then, each sample plot was transferred onto the LAI images, and the maximum, minimum, average, total, variation range and standard deviation variable values of the LAI of the sample plots were calculated for each month. The relationships between AGB and LAI variables for each month were modeled with multiple regression analysis. In addition, the relationships between AGB and LAI variables obtained for all months were also modeled with multiple regression analysis. A total of 12 multiple regression models were developed. The model determination coefficient (R2) for the multiple regression models developed according to months varies between 〖(R〗^2) 0,10 and 0,178. On the other hand, in the model that included data for all months, it was found to be 〖(R〗^2) 0,444. The fact that the regression models developed within the scope of this study can reach a usable level for pure red pine stands shows that more scientific studies are needed for this purpose.