The field inventory method provides the required data from crown cover status of forest trees, but this method is costly and time consumer. Nowadays, remote sensing imageries provides an opportunity to automatically analysis forest characteristics with a high accuracy and low costs. This study aimed to evaluate the results of applying template matching algorithm on aerial image of UltraCam-D to delineate and detect automatically the single tree crowns of Persian oak(Quercus brantii Lind) in comparison with the results of visual interpretation techniques and the filed measurement method of crown covers. After preprocessing of images, in a terrain with an area of 10 ha inside Yasuj forest park, 100 trees of Persian oak were selected randomly. The crown area of the selected trees was determined and calculated using visual interpretation in Arcview software and was accepted as the control data. Using the field inventory, the areas of the tree crowns were measured and the numbers of sprouts in each coppice form were counted. Using the field inventory, the areas of crowns of trees were measured and the numbers of sprouts in each coppice form were counted and recorded. Moreover, to delineate and recognize the crown of trees automatically, using programming in Matlab R2014b environment, the   template matching algorithm was applied on the mentioned images. The results showed that the accuracy of template matching algorithm is better than the method of field measurement and it was 4.91 percent of the control method. The overall accuracy and kappa coefficient between the automatic detection of crown peaks and the number of counted sprouts in each coppice form were 77 and 74 percent, respectively.