This paper proposes acoustic-phonetic features for classification of place-of-articulation of stop consonants derived from their temporal structures. The speech signal corresponding to a stop is characterized by several temporal features such as sub-band zero-crossings and envelope fits. Classification experiments on the stops from the TIMIT (read speech) and the Buckeye (conversational speech) databases using a support vector machine classifier demonstrate that the performance of the proposed features (84.6%) is comparable to that obtained by MFCCs (85.1%) in many aspects. Further, the classification accuracy is boosted (90.1%) with the combination of temporal and MFCC features, which substantiates their supplementary nature.