Investigating the capability of Landsat 8 OLI data for estimation of aboveground woody biomass of common hornbeam (Carpinus betulus L.) stands in Khyroud Forest

In this research, capability of Landsat 8 OLI was studied for estimation of aboveground biomass in pure stands of the common hornbeam (Carpinus betulus L.) in Hyrcanian forests of Iran. In order to obtain in situ aboveground biomass, diameters at breast height (DBH) of all trees greater than 7.5 cm were measured in 55 sample plots. Then, in situ aboveground biomass was calculated using local volume table and specific gravity in each plot. About 70 percentages of in situ measurements (40 sample plots) were used for modeling aboveground biomass based on Landsat 8 OLI data using different methods of stepwise regression, backward regression, artificial neural network, k-nearest neighbor and random forest. Validation of the models was done using 30 percentages of in situ measurements (15 sample plots). Based on the Pearson correlation coefficient, near-infrared band showed the highest correlation with aboveground biomass (0.52). Backward regression with adjusted R2 of 0.295 and RMSE% of 28.63%, and artificial neural network with RMSE% of 23.45% showed the best performance among parametric and non-parametric methods, respectively. Based on the results, Landsat 8 OLI data seems suitable for aboveground biomass estimation in pure stands of the common hornbeam only over large areas and small scale. Although more investigations are required to verify and generalize the results to the entire Hyrcanian forests of Iran.