Landslides are one of the main geological disasters that persist in the reservoir after the completion and dynamic water storage of the Three Gorges Dam, and it is a threat to the safety of the residents along the river and shipping. The increase of landslides around the reservoir is affected by the yearly cycle of impoundment and flood water discharged from the dam, and precipitation, etc. Hence, monitoring the reservoir accurately and timely is one of the essential means for preventing disasters like landslide in the Three Gorges. In this work, we apply the photogrammetry method to the field of landslide monitoring on the basis of previous methods. We develop a solving method of landslide displacement field based on the image gray feature matching. First, image capture equipment like camera, vidicon is utilized to photograph the dynamic and static fields or movement process so as to obtain the time series images. Then kinematic variables like position, velocity, acceleration and deformation variables like displacement and strain are calculated by analyzing the images with digital correlation method. The essential idea of the image gray feature matching method is based on the viewpoint of statistics. Images in this method are treated as two-dimensional signals for searching corresponding match between signals by using correlation method. We can match two images around the same site before and after the landslide and obtain the displacement of this point. The Woshaxi landslide of Zigui County, Hubei Province is chosen as the study object, and we obtain the displacement field over time and the displacement vector of the landslide. The overall displacement is up to 50 cm, and the value and direction of regional displacement of the landslide surface are not completely the same. The overall landslide surface move rightward in the horizontal direction, and slid downward to the river in the direction vertical to the flow direction of the river. The vertical displacement is relatively larger in comparison with the horizontal displacement. Therefore, landslide movement is a non-uniform and non-rigid body motion. By integrated use of the speckle method, gray feature search and other related serial methods, we succeed in dealing with landslide problems like small deformation relationship and large displacement movement. As a new observation method, this method also solves problems, such as the registration of collected images and the peering of gray level. We calculate the variation and direction of displacements of all points on the landslide and obtain the distribution map of the landslide displacement. The error in the indoor calibration test was within the acceptable range, which verified the validity of this method. The measuring method of the landslide displacement field proposed in this work possesses advantages of whole field, non-contact and flexible monitoring range like the traditional photogrammetry, as well as other advantages such as large deformation measuring range, good adaptability of environment, etc. Compared with the traditional point measurement method, this method may not only obtain displacement data of more landslide points, but also monitor the global deformation of the landslide and observe and predict the whole movement behavior of the landslide. This method bounds the observation range to every specific landslide, has higher displacement resolution, and is unconstrained by weather condition, attitude angle and flight cycle relative to the photogrammetry based on satellite images. More importantly, the cost of data acquisition is relatively low in this method. We can set up cameras at landslide points and realize unattended data acquisition and analysis, i.e., autonomic monitoring and early warning of landslide displacement. Consequently, this method has a good application prospect.