Monitoring of Land Cover Changes between 1990 and 2014 Over Cyprus Using Multi-Temporal Landsat Imagery

Determining changes in forest resources and land cover/land use is crucial for sustainable forest planning. This study aims to determine changes in land cover 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 images 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 classes generated based on the supervised classification were consolidated into five main classes. After the classification process, the accuracy of the classification for each image was determined. Accordingly, the overall classification accuracy of the map from the 1990 Landsat 5 TM satellite image was 92%, with 0.90 Kappa Statistics. The overall classification accuracy of the map from 2014 Landsat 8 OLI satellite image was 89.20%, with 0.87 Kappa statistics. Then, land cover change analysis was conducted to compare a twenty-four-year period within the study area.