The Magellan spacecraft SAR imaged 98% of the surface of Venus and unveiled a volcanically shaped landscape with a wide array of volcanic and tectonic features; predominantly a variety of weathered lava flows and plains of seemingly mafic composition. With the future observations of the newly approved EnVision and VERITAS missions to Venus, both carrying new-generation radar systems as main payload, image inter-comparison between the missions and with Magellan products, aiming at monitoring surface changes, is a unique opportunity, the first of its kind in Venus and with EO-level capabilities to another planet, to gather direct evidence of surface erosion, weathering, and volcanic eruptions. Comparison and analysis of SAR images between Magellan, EnVision and VERITAS is a challenging endeavor, considering the observational differences between the missions in terms of orbit, sensors’ resolution, viewing geometry and carrier frequency. Simulation of EnVision and VERITAS radar images by means of an empirical model that combines Magellan SAR and a variety of EO test data is the core study that will enable our understanding of the new missions’ capabilities in one hand, and the capacity to separate sensor-driven changes from real surface processes on the other. Such model can be refined and expanded once the data from the missions becomes available. Moreover, the SAR image intercomparison framework created will also help to expand incoherent change detection between different spaceborne SAR image sensors on Earth, a field that remains underexplored to date. In addition, simulating EnVision and VERITAS SAR images also enables the development of a series of tools, which can be put together in a single user interface for the science community: these include change detection algorithms, but also machine learning integration of data from all EnVision sensors to produce level-2 geomorphology products and stereographic tools for stereo imagery of EnVision’s radar VenSAR.
