Venus, often described as Earth’s closest planetary twin in terms of size and bulk composition, remains poorly understood with respect to its surface geology and geodynamic history. The dense carbon dioxide rich atmosphere, together with a persistent global cloud layer, prevents the use of optical sensors, making radar the only effective remote sensing tool for investigating the planet’s surface.

The NASA Magellan mission produced the first global radar maps, yet fundamental questions about resurfacing events, tectono-volcanic processes, and the relationship between interior dynamics, surface morphology, and atmospheric evolution are still unresolved. The surface of Venus exhibits striking landforms of high scientific interest, including extensive volcanic provinces, coronae associated with mantle upwellings, and ancient tesserae regions that preserve the oldest crustal records.

Understanding these terrains is crucial for constraining Venus’ geodynamic regime, evaluating the possibility of ongoing activity, and placing the planet within the broader context of comparative planetology and long-term climate evolution. The forthcoming ESA EnVision mission is designed to address these outstanding questions with a suite of instruments, of which the VenSAR radar is the cornerstone. Operating at S band (3.2 GHz), VenSAR will penetrate Venus’ atmosphere to obtain high-resolution imagery. Its dual polarimetric mode (HH and HV) will enable quantitative analysis of scattering mechanisms, dielectric variations, and surface roughness.

Such measurements can distinguish lava flows of differing emplacement history, identify subtle tectonic fabrics in tessera terrain, analyze deformation around coronae, and characterize the volcanic plains. The mission’s repeat pass capability will further permit polarimetric change detection, offering new opportunities to investigate active volcanism, crustal dynamics, and ongoing geological processes. To maximize scientific return, preparatory studies using terrestrial SAR missions such as Sentinel-1, ALOS-2, and the forthcoming NISAR are being carried out.

These datasets, combined with legacy Magellan observations, are applied to Earth analogues of Venusian terrains, particularly the volcanic landscapes of Iceland. The basaltic lava flows and volcanic constructs in Iceland closely mimic the morphology and radar scattering behavior of Venusian volcanism, making them ideal natural laboratories. These analogue studies support the refinement of polarimetric and interferometric techniques, improve strategies for surface classification, and enhance change detection methodologies in anticipation of VenSAR data.

In parallel, an open source processing toolkit is being developed specifically for these applications, designed to provide accessible methods for the wider planetary science community. A central methodological challenge is bridging the resolution gap between historical Magellan imagery and the forthcoming VenSAR observations, which complicates direct comparison and the formulation of reliable change detection metrics.

To overcome this, we propose a statistical framework based on fitting a generalized beta prime distribution to the intensity ratio histograms of paired SAR datasets. This approach accounts for conditions such as unequal numbers of looks, spatial correlation between pixels, and strong textural heterogeneity. By providing a mathematically consistent description of ratio statistics, the method enables reliable cross comparison of heterogeneous SAR datasets and ensures robust detection of surface changes.

Through the integration of terrestrial radar studies, analogue based investigations, and methodological advances in statistical change detection, this research lays the groundwork for maximizing the scientific return of EnVision’s VenSAR. These efforts will significantly improve our ability to characterize Venus’ surface, constrain its geodynamic activity, and advance our broader understanding of terrestrial planet evolution.