Lunar Orientale Impact Basin Secondary Craters: Spatial Distribution, Size‐Frequency Distribution, and Estimation of Fragment Size

Abstract

Secondary impact craters, features created by projectiles ejected from a primary impact, contain important information about the primary cratering event and the nature and distribution of its ejecta. The Orientale impact basin (D ~ 930 km) is the youngest and the least degraded large impact basin on the Moon and has the most recognizable secondary impact craters. We identified and mapped 2,728 secondary craters in the investigated area of ~1.66 × 107 km2, covering an area from the rim of Orientale to six radii. Secondary crater diameters range from ~2 to 27 km, and the median diameter decreases as distance increases. Secondary craters are concentrated predominantly in the northwest and southwest. The ejecta deposit pattern inferred from secondary crater distribution suggests that the Orientale basin was formed by an oblique impact in which the downrange direction was 240°–265° in azimuth, and the incidence angle was steeper than 20°. The cumulative size‐frequency distribution of mapped secondary craters steepens as diameter increases and is very well approximated with a Weibull distribution with an exponent 1.32. A widely used crater scaling relationship predicts that the fragments that produced the secondary craters were predominantly in ~0.5–2‐km diameter range over the investigated area; the diameter of the largest fragment, however, decreases with increasing distance from Orientale. On the basis of the diameter of the largest secondary crater of Orientale, and other craters and basins, the largest secondary crater of the South Pole‐Aitken basin is estimated to be ~40 km in diameter. We explore the implications of these findings for the evolution of the megaregolith and future sample return missions.

Rock Abundance and Crater Density in the Candidate Chang'E‐5 Landing Region on the Moon

“…In cratering chronology, secondary craters add ambiguities in age estimation, and therefore, they must be excluded before dating the surface age. To minimize the influence of secondary craters, only relatively large craters (≥500 m in diameter) were used for the SFD analysis, and for craters larger than 500 m, a manual checking process was further carried out to remove possible secondary craters based on clues such as clustering distribution and visual distinctness from primary craters (Guo et al, 2018;Robbins & Hynek, 2014;Wilhelms et al, 1987). To minimize the influence of secondary craters, only relatively large craters (≥500 m in diameter) were used for the SFD analysis, and for craters larger than 500 m, a manual checking process was further carried out to remove possible secondary craters based on clues such as clustering distribution and visual distinctness from primary craters (Guo et al, 2018;Robbins & Hynek, 2014;Wilhelms et al, 1987).…”

“…The secondary craters in the candidate landing region are basically caused by ejecta from three primary craters: Copernicus, Harpalus, and Pythagoras (Qian et al, 2018;Scott & Eggleton, 1973). To minimize the influence of secondary craters, only relatively large craters (≥500 m in diameter) were used for the SFD analysis, and for craters larger than 500 m, a manual checking process was further carried out to remove possible secondary craters based on clues such as clustering distribution and visual distinctness from primary craters (Guo et al, 2018;Robbins & Hynek, 2014;Wilhelms et al, 1987). The estimated surface ages of the geologic units in the candidate landing region are shown in Figure 7a, and the cumulative crater size-frequency plots for each unit are shown in Figure 7b.…”

A Machine Learning Approach to Crater Classification from Topographic Data

“…On the one hand, it provides an opportunity to get a more precise geological age through the crater size-frequency distribution (CSFD) method. Making up a great percentage of small craters [7], secondary craters often lead to considerable uncertainty in the CSFD method [1,4,[8][9][10][11][12]. Distinguishing primary from secondary craters is helpful in counting primary craters, hence improving the accuracy of crater dating.…”

“…On the other hand, identification of primary and secondary craters also has a significant effect on projects concerning impact distribution, which may suggest diverse rotation. Besides, secondary craters also provide an approach to understand the impact characteristics of their parent craters.Researchers have tried to distinguish primary craters from secondary craters, and identifying and learning the differences in their characteristics is the foundation of all related studies [1,13]. These differences play an important role in the distinguishing effort.…”

“…Researchers also found that primary and secondary craters also differ in rock size and center mound, which may be useful for distinguishing the two [20][21][22].Similar to crater detection, current methods aiming at distinguishing primary craters from secondary craters include manual and automatic techniques. Compared with the great progress made in automatic crater detection, however, manual identification is still the method used in the most recent works related to distinguishing primary craters from secondary craters [1,[23][24][25][26], and very few works have tried to develop a useful automatic approach [5,10,[27][28][29][30]. Distinguishing primary craters from secondary craters manually can give accurate results, but it requires a lot of time and expert knowledge.…”