Estimation of some forest stand parameters using different satellite images: Case Studies from Kelkit and İğdir Planning Units

Accurate and up-to-date information on forest composition and structure is essential for effective management, yet conventional inventory methods require considerable time, labor, and cost. Remote sensing provides an efficient alternative by enabling the estimation of stand parameters through reliable and rapid techniques. This study investigates the relationships between remotely sensed data and key stand parameters—including number of trees, basal area, and volume—measured from field sample plots in even-aged pure Scots pine (Pinus sylvestris) stands and uneven-aged pure fir (Abies nordmanniana subsp. bornmuelleriana) stands. Research was conducted in Kelkit/Gümüşhane, dominated by Pinus sylvestris, and İğdir/Kastamonu, characterized by Abies nordmanniana subsp. bornmuelleriana. Five different remote sensing datasets were employed, including Göktürk-2, Rasat, and aerial photographs captured with digital cameras, which had not previously been applied for similar purposes. Using multiple regression analysis in SPSS 20.0, relationships between stand parameters and satellite reflectance/pixel values, along with vegetation indices derived from ERDAS Imagine, were evaluated. Results indicated that Landsat 8 imagery produced the most accurate estimations for all parameters in both regions. The adjusted R² values for volume, basal area, and tree number were 0.44, 0.77, and 0.77, respectively, in Kelkit, and 0.60, 0.75, and 0.80 in İğdir. Models with the highest coefficients of determination and lowest standard errors were selected and applied to both study areas. Final outputs were compared with the existing stand type maps, demonstrating the effectiveness of remote sensing in improving forest inventory and management.