The row structure of crops as a typical periodic feature of the cultivated land surface， and its direction will can significantly affect the results of radar backscatter coefficients and optical reflectivity. The key problem of low extraction efficiency and large demand for computational resources when using the texture features of high-resolution remote sensing images to extract crop row direction， it is difficult to be applied on a large scale. In this paper， the feasibility of using the morphological characteristics of the plot to identify the row direction of crops was verified with the premise that the plot was the minimum research object， based on the YouYi County of Heilongjiang Province as the research area. The algorithm uses a variety of images processing algorithms to calculate the length ratio （aspect ratio） between the long side and the short side of the plot， analyzes the relationships between the row direction of the crop and the direction of the long side and the influence of the aspect ratio of different plots on the recognition rate and accuracy. The results show that： With the increase of plot aspect ratio threshold， the recognition rate of row direction decreased from 82.0% to 34.8% ， and the Root Mean Square Error （RMSE） of row direction recognition decreased from 21.46 ° to 1.78°； Under different aspect ratio thresholds， the average accuracy of Line Segment Detector （LSD） algorithm in identifying crop row direction （determination coefficient R2=0.93， RMSE=9.53°） is higher than that of probabilistic Hough transform （R2=0.81， RMSE=20.80°） ； The approach proposed in this paper can effectively achieve the identification of crop row direction in a large range of farmland plots， which provide a new idea for the research of remote sensing satellite images in identifying crop row direction.