Surface geological evolution in the Chang’e 5 landing area (Em4 unit) revealed by a new age-retrieving method from regression learning

The chronology function and production function have been widely used to derive the model ages of lunar mare regions from crater size-frequency distributions (CSFDs). Challenges remain in homogenous counting area selection, crater saturation and crater rim identification. Geological unit-based ages are also difficult to study the continuous surface evolution among adjacent areas. Using regression-learning models, we have tried a new method on the Em4 unit of the Chang’e 5 landing area to explore a quantitative relationship between ages and surface morphometric expressions by using texture features. Four features (Contrast, Energy, Entropy and Homogeneity), together with a stepwise linear model (SL) and a linear support-vector-machine model (LS) are well selected to produce a pixel-level continuous age map of the Em4 unit. Mean age values of 1.75 ±0.26 Ga and 1.69 ±0.22 Ga obtained respectively from the two models are consistent with the ages of Chang’e 5 samples returned from this area. Both texture features and age maps are separated along the NW-SE sinuous rilles (Rima Sharp and Rima Mairan). Comprehensively considering geology, geomorphology, and newly retrieved ages of the study region, we have proposed a three-stage evolution process for the Em4 unit. Our new age-retrieving method is useful to obtain a pixel-level high-resolution age map in the study region and has the potential to be widely used in other lunar mare areas.