Abstract: This study introduces a new approach for utilizing the neural network for surface current simulation from RADARSAT-1 SAR image. The neural network input is a vector containing the values of the RADARSAT-1 SAR image intensity gradients. In this study, a single feed forward -propagation neural network was utilized to estimate the Doppler frequency shift in order to determine the surface current pattern along RADARSAT-1 SAR image. It is found that, the neural network outperformed conventional regression technique in modeling surface current velocity and their directions. The RMSE detected from NN model was 0.18 m/s. The reduction of the amount of the errors is due to good performance of regression model.