The autonomous path planning and landing of unmanned aerial vehicles in open scenes has been the focus of research in related fields. We propose a method based on the point cloud data collected by the lidar to recommend the optimal landing address for the UAV. This method corrects and expands the original point cloud data by using the UAV pose information and maintaining the site selection window, then we propose to improve the RANSAC algorithm to evaluate and select the generated candidate planes, and finally output the coordinate information of the optimal landing site. The experiments in the simulation environment show that the results of this method are stable and accurate, and the computational speed satifies the requirements of the UAV to work in real time. At the same time, the space and time cost of this method is light, which meets the standard of the operation in real scenes.