Shahram Yousefi Khanghah
Department of Range and Watershed Management, Behbahan Khatam Alanbia Tecnology of University, Behbahan, Iran
Key words: Vegetation Type, Satellite data, Classification, Rangeland.
Remote sensing assessment is used along with field data to enhance sampling and site representation. The research was carried out in Ameri region located between 50° 05´ to 50° 16´ east longitude and 30° 03´ to 30° 13´ north latitude in south west of Iran, as a dry Climate and located in the coastal region with 15915 hectare area. The aim of the present research was to produce rangeland vegetation types using satellite data. Geometric corrections of images were applied using ground control points (GCP) and geo-referenced images with root mean square error (RMSE) less than one pixel, then images Co-registered together with RMSE less than 0.2 pixels. The atmospheric corrections of images were applied using Cost method. Image spatial resolution enhanced using fusion with a panchromatic band. Images classified using maximum likelihood (ML) algorithm of supervised classification with 100 training area, and produced five rangeland vegetation types, then accuracy of produced maps determined with ground truth samples. The results show that both sensors can produce suitable vegetation type’s map in study area, and ML classification method able to delineate rangeland vegetation type’s map with acceptable precision. As a result we imply that visual interpretation and manual mapping will be used to delineate vegetation type’s maps of arid rangelands.