Abstract: Satellite remote sensing technology serves as an important means to monitor the sea ice in Polar Regions at present.With the continuous optimization of satellite data, the appropriate algorithm may improve the accuracy of sea ice drift monitoring, which has the important significance to the researches of polar sea ice motion in China.This study obtained a more accurate data set through an effective preprocessing method based on Sentinel-1 remote sensing data.Additionally, the SIFT (Scale-Invariant Feature Transform) feature tracking method was used to realize the monitoring of the velocity and orientation of the sea ice drifting in polar regions with a time interval of one day based on the previous data set.Finally, this method was validated by buoy data.The results suggest that the drift vector obtained in this study is consistent with that obtained from buoy data, which indicates that the method can effectively realize the detection of sea ice monitoring in the polar regions with high accuracy(the average error ratio is 8.1% compared with the buoy data).