The increasing land use changes leading to urban expansion have attracted the researches. Urbanization has become a recent growing trend in many cities around the world. In most cases to estimate the urban expansion with the conventional survey and mapping techniques is expensive and time consuming. Remote sensing is increasingly used for detection and analysis of urban expansion since it is cost effective and technologically efficient. This paper aims to give the taxonomy of various methods and techniques to analyze the land use change detection through remote sensing images in an effective manner. One of the most important functions of remote sensing data is Land Use and Land Cover maps managed through image classification. This describes the various classifiers, software and image digitization techniques that are used in estimating the urban changes. Wide database of images has been used to test the algorithms. Hence, an in-depth study of existing work related to land use change detection will help to accelerate research in the field of urban change. This paper presents a systematic analysis of work done in land use change detection area. We also present a Comparison of existing methods and techniques used for land use change detection. Based on this analysis, we finally presented a few future research directions related to land use change detection through remote sensing images, which will be reduce uncertainties in the image-processing chain to improve classification accuracy.