The identification of the topographic features of the transmission line is an important issue to realize the cost estimation and safety design of the transmission line. In order to solve the problem of rapid identification of terrain features in digital transmission lines applications, a deep autoencoder-based terrain feature extraction method is studied. First, a digital model of complex geographic information is established based on digital exploration technology, and then the algorithm structure of the deep autoencoder is established. The layer-by-layer training method is used to solve the problems of gradient disappearance and gradient explosion in the deep autoencoder. Moreover, in the actual example, the particle swarm optimization algorithm is used to adjust the hyperparameters of the deep autoencoder. Experimental results show that the proposed method can classify different landforms rapidly, and the results can assist designers in the cost estimation and safety design of transmission lines.