This study aims to classify Landsat 8 satellite data using NDVI thresholds. Initially, visible and near infrared bands of Landsat 8 satellite were used to derive Normalized Different Vegetation Index (NDVI) image. Vegetation, non-vegetation and water areas were then analyzed where thresholds for separating them are carefully determined with the aid of ground truth information of the study area. Density slicing was performed in order to separate the image into different land covers. Eventually, color mapping and class labeling were done to complete the classification process. The accuracy of the classified image is then assessed using a confusion matrix where overall classification accuracy and Kappa coefficient are computed. The result shows that NDVI-based classification is able to classify the Landsat 8 satellite data with a high accuracy.