In this research, the capability of Rapid Eye satellite imagery for mapping the crown distribution of oak trees in Zagros forests was investigated in the Dashtebarm forest area of Kazeroun, Fars province. In this study, data quality was investigated geometrically and radiometrically and geometric correction of the images was done using a linear method and using precision ground control points. In order to investigate the use of artificial bands obtained from appropriate processes in the classification process, images of appropriate plant spectrum indices were created by mapping the bands and images of the main components using the principal components analysis (PCA index). The vegetation map of crowns of trees was measured by measuring the crowns of trees in square sample samples with an area of 400 square meters in a randomized way. 70% of samples were selected as educational sample and 30% of the rest were randomly selected. Two-point and polygonal classification with two maximum likelihood algorithms and support vector machines was performed on the original image, the processed bands, and the main image composition of the processed bands. The results of the accuracy assessment of the maps in this study showed that the highest overall accuracy and Kappa coefficient were 98.52% and 0.97, respectively, in the point of processing with processed bands and maximum likelihood algorithms, as well as with the image composition The original is with processed bands and support vector machines algorithm (SVM). Also, in the polygonal classification, the highest overall accuracy and kappa coefficient of the maps classified using the processed bands were 87.50% and 0.75 with the maximum likelihood algorithm and 90.78% and coefficient Kappa 0.81 has been supported by the car engine algorithm. In general, the results of this study showed that Rapid Eye images are suitable for preparing the crown distribution map of forest trees in Zagros forests.
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