A strain tensor analysis plays an essential role in geophysics and engineering applications since it provides a numerical measure on the relative deformation behavior of the object under investigation. The parameters in a strain tensor can be estimated by observing the positional coordinates of the deforming network at different epochs. Consequently, the quality of a strain analysis is highly dependent on the network configuration. Most of the previous studies regarding network design have focused themselves on point displacements rather than on network strains. In this study, a strain sensitivity index – the minimum detectable principal strain parameter has been developed based on the concept of the invariant function and statistical theory. From numerical tests, it has been proven that the proposed sensitivity index realistically reflects the capability of a network in monitoring potential strains, and thus can be used as a concrete measure for the optimization of a monitoring network. In real-case applications, the strain sensitivity analysis has been performed on the first-order satellite network in Taiwan. Results reveal that the coastal areas have a lower sensitivity in detecting surface strains due to a poor network configuration. On the other hand, it has also been illustrated that, by incorporating the network optimization guidelines developed in this study, the strain sensitivity index can be substantially improved in these areas.