Evaluation of Different Enhancement Remote Sensing Techniques

Knowledge of agricultural and horticultural land use percent is necessarily important for supplying human food and should be considered in agricultural planning. Remote sensing provides valuable data on land use classes. Mapping land use through remotely sensed images comprises various considerations, processes and techniques. In this research, different enhancement techniques have been utilized for extraction of irrigated land class in a part of Hablehrood watershed. The results of this investigation showed that among the studied techniques; ICA algorithm which can be viewed as a nonlinear generalization of Principal Components Analysis has the highest accuracy, whereas supervised classification has the lowest accuracy. Moreover; this research revealed that NDVI accuracy is more than Tasseled Cap. So, the Irrigated land class of the study area based on ICA technique with the most accuracy was 1272.37 hectares.