Aim. This study evaluates the use of Ordinary Kriging, a geostatistical method, for estimating the basal area index in coppice oak forests of northern Zagros, Iran. Methodology. The research was conducted in a 6,103-hectare coppice oak forest in northern Zagros, Iran, dominated by Quercus brantii alongside other species. A systematic-random grid was used to establish 136 sample plots (0.1 ha each), where diameter at breast height (DBH) was measured to calculate basal area. Exploratory data analysis assessed normality and trends, while variogram analysis determined spatial structure. Ordinary Kriging was applied to predict basal area, with accuracy evaluated through cross-validation using statistical metrics (MAE, RMSE, and their relative values). Results. The forest exhibited a low basal area (14.53 m²/ha) despite high tree density (350 stems/ha), indicating dominance of young trees and coppices. Variogram analysis revealed strong spatial dependence (SDD = 99.8%), with an exponential model best fitting the data (r² = 0.676). Ordinary Kriging provided accurate predictions (MAE = 1.25 m²/ha, RMSE = 3.26 m²/ha), confirming its reliability for spatial estimation. Research implications. The findings demonstrate that geostatistical methods like Ordinary Kriging offer a precise and efficient alternative to traditional forest inventories, enhancing sustainable management. The strong spatial dependence of basal area supports its use as a regionalized variable, aiding in optimized sampling strategies. Practically, this approach can improve forest resource assessment, carbon stock estimation, and conservation planning in ecologically vital ecosystems like the Zagros oak forests.
