<p>The Chhotanagpur Plateau is the eastern part of the Indian shield, which is renowned for its diverse geological and unique terrain features and is also known as the storehouse of valuable Precambrian rocks and minerals. Landform classification is very useful for illustrating the evolutionary background of any region, sustainable land use planning and natural hazards management. The objective of this study is to classify the landforms of the Chhotanagpur Plateau region by applying a Support Vector Machine (SVM) based classification technique using a grid digital elevation model (DEM). The SVM-based grid DEM landform classification method identifies different landforms, namely highland with ridges, highland with escarpment, highland with hills, valley margin, river valley, high elevation plain and low elevation plain. The result shows that this method is most efficient in identifying the low elevation plain with 99.32% accuracy, followed by river valley (99.24%), high elevation plain (98.53%), highland with ridges (98.51%), and hills (98.41%), valley margin (97.98%) and highland with escarpment (96.25%). The kappa coefficient and model evaluation index F1-score verify that the method and model are reliable when applied to grid DEM-based landform classification problems. The result has also been verified through field verification techniques with the help of GPS data. This high-accuracy map should be applied for regional planning and natural hazards management. These techniques also give very good results for terrain classification as well as landform evolution.</p>