Abstract
Understanding plant cover performance in a region is one of the most important factors in controlling soil fertility and its management. In studying plant cover by using of traditional field data collection methods are difficult and time consuming. Using of GIS data in vegetation cover studies satellite images can be helpful in reducing of time and obtaining more precise information. In this study different aspects were considered to obtain the best composite of different indices and identifying the most suitable parameters. The related bands obtained from tasseled cap, principal components analysis and the calculated indices were also used to evaluate the role and effects of different filters on Landsat ETM+ of Neyshabour region. Regression equation and regression coefficients of different parameters were analyzed and evaluated. Finally the most applicable indices were compared with the classes obtained from image classification. The results showed that mean filter of 3×3 has higher correlation coefficients when digital numbers were compared with field collected data. The indices of MSR,VI5, VI6, VI1, RI, BI1, SI, NDVI,TVI ,NDSI ,SAVI,MND, MSAVI, Complex multiratoو COSRI and also PCA1 and the PCA3 obtained from principal components analyses, brightness and greenness bands received from tasseled cap conversion are providing better recognition and evaluation of plant cover in the region.

Keywords: Vegetation indices, Principal components analysis, Tasseled cap, Image classification, Landsat