Determining changes in forest resources and, consequently, land cover/land use is crucial for sustainable forest planning. This study aims to determine changes in land use classes, including Forest areas, Agricultural areas, Settlement areas, Other non-forest areas, and Water bodies in the study area located in Cyprus between 1990 and 2014. The study utilized digital management plans, a high-resolution base map, and Landsat satellite data for the relevant years. Necessary preprocessing steps were applied to prepare the satellite data for classification. Initially, unsupervised classification was conducted on the images to determine the number of distinguishable sub-information classes. Subsequently, supervised classification was performed using the maximum likelihood algorithm with the provision of training areas. The sub-information classes obtained from the supervised classification were consolidated into five predetermined main information classes. Following the classification process, the accuracy of the classification for each image was determined. Accordingly, the classification accuracy of the 1990 Landsat 5 TM satellite image was found to be 92% (Overall Classification Accuracy: 92%, Overall Kappa Statistics: 0.9000), while the classification accuracy of the 2014 Landsat 8 OLI satellite image was 89.20% (Overall Classification Accuracy: 89.20%, Overall Kappa Statistics: 0.8650). Subsequently, change analysis was conducted using the post-classification comparison method, and changes in land use within the study area over a twenty-four-year period were examined.