عنوان مقاله [English]
The remotely sensed data is one of the most rapid methods for providing thematic maps in natural resources, especially forest. By combining ETM+ data and ground observation data, we can have access to thematic maps of forest such as canopy cover map, that it can be used in forest ecological studies and forest management and improvement.
The research was conducted to evaluate and investigate the possibility of using Landsat7 ETM+ data for developing forest canopy cover density map at four classes in four sites of Caspian Forests of Iran.
Based on OIF index and statistical analysis of the ETM+ data, Color composite 3, 4, 5 were selected for unsupervised and supervised classifications. Ground observation information was collected from 282 plots (150*150m), using unsupervised map as a primary map.
Finally, combining the ETM+ data and the ground information, using supervised classification method, canopy cover map was achieved at four classes (5-30%, 31-50%, 51-80%, 81-100%).
Evaluation of the canopy cover density percentage showed that the overall accuracy of the canopy cover percentage map developed by the Landsat7 ETM+ data and average accuracy, producer's and user's accuracy were: 85.43, 84.7 and 82.68 percent, respectively.