Data mining techniques have been widely used for extracting knowledge from large amounts of data. Monitoring deforestation is utmost important for the developing countries. Classification of deforestation is one of the primary objectives in the analysis of remotely sensed data. The present study focuses on monitoring accurate results of deforestation and forest degradation using classification techniques. In this paper, an experiment has been set up on different classification algorithms to compare the results. To evaluate the results, the authors used the WEKA open source tool, which is a collection of machine learning algorithms consisting of different processing tasks such as classification, association and clustering.