Small lunar craters at the Apollo 16 and 17 landing sites - morphology and degradation

New analysis and modeling approaches are applied to high-resolution images and topography of the Apollo 16 and 17 landing sites to investigate the morphology and estimate degradation of small lunar craters (SLCs; 35 to 250  m diameter). We find SLCs at the two sites are mostly degraded with an average depth-diameter ratio (dD)<0.1, resulting in a landscape dominated by shallow, inverted cone-shaped craters. An improved standardized morphological classification and a novel set of quantitative shape indicators are defined and used to compare SLCs between the two sites. Our classification methodology allows morphological class populations to be designated with minimal (and measurable) ambiguity simplifying the study of SLC degradation at different target regions. SLC shape indicators are computationally obtained from topography, further facilitating a quantitative and repeatable comparison across study areas. Our results indicate that the interior slopes of SLCs evolve faster and through different processes relative to larger craters ( > 500 m). Assuming SLCs are formed with large initial depth-to-diameter ratio (dD≥0.2), our observation that even the fresher SLCs are relatively shallow imply that a faster mass wasting process post-formation stabilizes the crater walls and eventually slows down degradation. We also found that the Apollo 16 Cayley plains have a higher percentage of fresh craters than the Apollo 17 Taurus Littrow (TL) plains. A combination of a less-cohesive target material and/or seismic shaking resulting from moonquakes or the impact of Tycho crater secondaries was likely responsible for a higher degradation rate in the TL-plains compared to the Cayley plains. This study explores the relationship between the symmetry and probability densities of key morphological traits like dD, mean wall slope and rate of degradation. We show that the shape of dD probability density function of SLCs in a study area encodes their rate of degradation. Comparison of power-law fitting and probabilistic modeling of depth-diameter relations shows that probabilistic methods complement regression models and are necessary for robust prediction of SLC depths from diameter (and vice versa) for different geological targets.