Potential of Bidirectional Long Short-Term Memory Networks for Crop Classification with Multitemporal Remote Sensing Images

The Bi-LSTM could compensate for the information deficiency by including temporal information from both forward and backward states, thereby achieving the best classification accuracy, compared with the unidirectional LSTM.