Remote sensing data are important data sources in the management and planning of forest ecosystems. In this study, we aimed to estimate forest stand parameters using the spectral (Average Brightness Value) and textural features (Standard Deviation of Gray Levels, Entropy, Contrast, Correlation, Homogeneity) derived from digital aerial images. Study was carried out in Adiyaman Forestry Operation Directorate in Turkey. Relationships between image features and stand parameters (diameter at breast height-DBH, mean height, stand volume, basal area, and number of trees) were tested by using Pearson's correlation coefficient. Image features exhibiting the highest correlation with stand parameters were modelled by a linear regression analysis. The validity of the models developed was then tested using the leave-one-out cross-validation method. The 'Contrast' values derived from the infrared band showed the highest correlation with DBH and mean height, the 'Contrast' values from the red band showed the highest correlation with stand volume and basal area, and the 'Homogeneity' values from the infrared band showed the highest correlation with the number of trees. The adjusted coefficients of determination (R(2)adj) of the estimation models were calculated 0.48 for DBH, 0.38 for mean height, 0.41 for stand volume, 0.45 for basal area and 0.43 for tree number. The relative root mean square error (RMSE%) values were for each parameters 11.91%, 23.57%, 20.96%, 15.81% and 16.20%, respectively.