The Kriging method is widely used for the spatial interpolation. However, the conventional Kriging method which only considers a singer factor generally leads to a considerable inaccuracy. In this paper, a cooperative kriging method based on particle swarm optimization is proposed to estimate the soil thickness distribution. Estimation is divided into two steps. Firstly, the particle swarm optimization is used to fit the semi-variance function. Secondly, the cooperative Kriging method which uses the altitude as an auxiliary variable is employed for estimation. In addition, a root mean square error is obtained to evaluate the estimation uncertainty of soil thickness. The proposed method is applied to estimate the soil thickness of a slope in Wansheng, Chongqing. It shows that compared with the conventional method, the cooperative Kriging approach improves the estimation accuracy by reducing the standard deviation by 39.32%, indicating that the proposed method is advantageous in improving the accuracy of spatial interpolation.