Safe, autonomous mobility in rough terrain is an important requirement for planetary exploration rovers. Knowledge of local terrain properties is critical to ensure a rover's safety on slopes and uneven surfaces. This paper presents a method to classify terrain based on vibrations induced in the rover structure by wheel-terrain interaction during driving. Vibrations are measured using an accelerometer on the rover structure. The classifier is trained using labeled vibration data during an off-line learning phase. Linear discriminant analysis is used for on-line identification of terrain classes such as sand, gravel, or clay. This approach is experimentally validated on a laboratory testbed.