An algorithm was proposed to investigate the feasibility of using stereovision to estimate the heading direction of a moving vehicle in open agricultural field environments. The algorithm first detected and tracked static natural ground features in two consecutive image frames taken by a vehicle-mounted stereo camera while the vehicle was in motion. Then, these static features were used as references to calculate the three-dimensional (3D) motion of the vehicle. Finally, the heading direction of the vehicle was estimated from the 3D motion. Working with a series of sequential image frames taken while the vehicle was in motion, the algorithm was able to generate a continuous estimation for the heading direction of the vehicle. Field tests were conducted to evaluate its usability. Due to the limitation of current experimental equipments, only the lateral motion of the vehicle was quantitatively evaluated. When the vehicle traveled straight forward, the proposed algorithm provided an accurate estimation for its lateral motion. When the vehicle traveled in an oscillating mode, the algorithm was able to respond the turnings of the vehicle immediately and correctly; the lateral motion estimation accuracy was inferior to that of the straight mode, but acceptable. Although the front direction motion of the vehicle could not be quantitatively evaluated, the current results still supported the research goal; because in plowing or planting operations, an accurate measurement of the vehicle's lateral motion could be an effective control parameter to keep a vehicle in a constant heading direction. Therefore, this research showed that it was feasible to use stereovision to estimate the heading direction of a moving vehicle in an open agricultural field.