Remote Sensing Images (RSIs) are rich in quantitative and qualitative information. A single RSI is worth millions of acres of land area. The RSI is only valuable once mapped into Land Use and Land Cover (LULC). The LULC is achieved through different techniques; classification is one such method which classifies the terrestrial features into respective classes and labels them. This study focuses on Remote Sensing Image classification and different classification methods.