Preparing Mighan wetland Land-use mapping in 2013: Using supervised and fuzzy classification methods

Revealing changes is one the most fundamental needs in the management and assessment of natural resources. With regard to remote sensing images، it is then possible to prepare land-use change maps، which are the result of the change detection processes. It should be noted that different methods have been presented to detect changes and developments of land-uses. The purpose of this study is prepared Mighan wetland –land use mapping in 2013 and Comparison of supervised and fuzzy classification methods. In this study، Mighan Wetland changes as well as its land-use and land-cover improvements were obtained through using OLI Landsat satellite images in 2013. Then، the images were geometrically and radiometrically corrected using appropriate algorithms. Subsequently، training samples were classified in five land-use classes based on fuzzy and supervised classification methods. After applying fuzzy classification and land use map was prepared on the Satellite image OLI. The classification accuracy was evaluated were to do a statistical profile accuracy and precision manufacturer for each of the classes was determined using Finally، the overall accuracy، the accuracy of the maps fuzzy and supervised classification was determined. Evaluating the accuracy of these two methods through determining the overall accuracy the results revealed that supervised method with an overall accuracy of 84. 91 and kappa value of 0. 7861 is more accurate than the fuzzy method with an overall accuracy of 83. 49 and kappa value of 0. 7667.