Landslides can be affected by transient deformation, which can be difficult to measure, particularly for landslides in remote locations. Because these movements can be precursors to ruptures, monitoring landslides with high frequency satellite data is a key objective of research in mountain landslide hazards. The PlanetScope constellation, with a daily revisit frequency, has a demonstrated capability for tracking surface motion based on the correlation of image pairs. However, the results of the image correlations are affected by a series of artifacts coming from the acquisition geometry, acquisition timing, pair-choice strategy or type of matching algorithm. The choice of these strategies and algorithms has not been validated quantitatively by independent measurements from moving areas, and no integrated and validated workflow is yet available to process the whole chain of data. In this context, we propose an integrated, open-source, and containerized software for calculating displacement fields using PlanetScope imagery. We used several years of GNSS data from two monitored slow-moving landslides in Peru to evaluate the strategies of image pairing and correlation algorithms (block matching - BM and more global matching - MGM). We first show that commonly estimated errors on stable areas are substantially underestimating the errors on moving areas. We then show that the image acquisition timing within the day significantly impacts the results due to illumination effects. By combining these results, we show that both the BM and MGM algorithms can perform well, but the BM algorithm appears to be more effective at capturing fast-moving objects, while the MGM algorithm gives better results in low-velocity areas and reduces systematic errors. We also show the benefits of combining short-term pairs (<3 months) with long-term pairs (yearly) for a better mapping of transient movements. The strategies were applied to three Peruvian landslides and demonstrated that effective parameterization allows for the accurate capture of their transient spatio-temporal kinematic responses to three external forcing factors: fluvial erosion at the landslide toe, material supply from scarp retrogression, and earthquakes. These findings demonstrate the possibility and advantages of using PlanetScope's satellites for operational landslide monitoring and for studying internal mechanical interactions within slow-moving landslides.