This work's primary goal is to identify the LULC classes for the Ujjain district. The analysis made advantage of the multispectrum satellite image. The work is based on pixel-by-pixel supervised categorization of Landsat satellite photos from 2003 and 2023 using the Arc-GIS tool throughout the course of two decades, employing the maximum likelihood approach and support vector machines. Areas of populated areas, water bodies, agricultural land, forests and arid terrain are among the different classifications of land use and land cover aspects that are considered to forecast the general changes. To achieve this purpose, remotely sensed Landsat 5 images from 2003 and Landsat 8 images from 2023 were used to identify changes. This work explains how the LULC classes for the ujjain region are compared by maximum likelihood algorithm and support vector machine algorithm. The result validation is done for MLC and SVM supervised classification and found kappa coefficient 0.809 and 0.844 respectively. Given their proven capacity to yield dependable cover outcomes, the SVM techniques ought to be particularly helpful in the categorization of land cover.