The aim of this study is to find out the combination of effective transformed data, applying Remote Sensing techniques, as to the classification and particular objects by transforming the MSS data and TM data of the satellite LANDSAT into several linearly transformed data. Since one of the problems in the processing of the LANDSAT data is the vastness of the data, the Linear Transformation could be a method to perform analysis of those vast data, more efficiently and economically. This method is carried out as follows : (1) offering the simplicity over complex data, (2) selectional processing over redundant data and removing unnecessary data, (3) emphasizing on the object of the study ; by transforming multispectral data through linear calculation and statistical transformation. In this study, the analysis and transformation of the data have been performed by means of Band Ratioing and Principal Component Analysis. As the classificatory consequence, Infrared/RED Ratioing which expands the characterization of green vegetation, has been useful for a distinctive classification among other classes. For the Principal Component Analysis, band 1,2,7 are efficient in the classification of the green vegetation.