Today, most geodetic networks established in landslide areas are being measured by differential Global Positioning System (GPS) measurements. Accuracy of differential GPS measurements now is capable of detecting real time displacements of geodetic control points in a landslide area. Nevertheless, producing optimal baseline configuration and optimal baseline weights in designing stage are necessary pre-requisites for an accurate geodetic GPS landslide monitoring network. GPS landslide monitoring networks should ensure the homogeneity and isotropy conditions, with regard to accuracy. Homogenous and isotropic geodetic networks ensured by criterion matrices, are established in landslide areas, and lead to minimize the coordinate errors in all directions in the same proportion. It is vital to provide applicable and reliable optimization results in the design stage of geodetic GPS networks for landslide investigations by forming a criterion matrix that leads to homogenous and isotropic networks. Analytical optimization methods are known as Second Order Design (SOD) strategies. In this study, an application of SOD, Direct Approximation of the Inverse Criterion Matrix, referred to as the U, in approximation method was applied to a landslide tracking network in Macka County in the province of Trabzon in the north-east of Turkey. The results of U,m approximation method were compared and analyzed with respect to the approximation quality of the criterion matrix. The results of the study showed that U,m approximation method is capable of reaching the target of a homogenous and isotropic geodetic GPS network. U,m approximation method produced not only the optimal weights of baselines, but also the optimal baseline configuration of the network. In conclusion, U,m approximation method is appropriate for optimization of geodetic GPS network, established in landslide areas. Also, the criterion matrix, that is willing to be reached as the result of the optimization, should provide the conditions of homogeneity and isotropy, with regard to accuracy of point coordinates. Thus, even minute deformation rates can be determined statistically significant by utilizing the optimum GPS network configuration.