Analysis of impact crater populations and the geochronology of planetary surfaces in the inner solar system

Abstract

Analyzing the density of impact craters on planetary surfaces is the only known technique for learning their ages remotely. As a result, crater statistics have been widely analyzed on the terrestrial planets, since the timing and rates of activity are critical to understanding geologic process and history. On the Moon, the samples obtained by the Apollo and Luna missions provide critical calibration points for cratering chronology. On Mercury, Venus, and Mars, there are no similarly firm anchors for cratering rates, but chronology models have been established by extrapolating from the lunar record or by estimating their impactor fluxes in other ways. This review provides a current perspective on crater population measurements and their chronological interpretation. Emphasis is placed on how ages derived from crater statistics may be contingent on assumptions that need to be considered critically. In addition, ages estimated from crater populations are somewhat different than ages from more familiar geochronology tools (e.g., radiometric dating). Resurfacing processes that remove craters from the observed population are particularly challenging to account for, since they can introduce geologic uncertainty into results or destroy information about the formation age of a surface. Regardless of these challenges, crater statistics measurements have resulted in successful predictions later verified by other techniques, including the age of the lunar maria, the existence of a period of heavy bombardment in the Moon's first billion years, and young volcanism on Mars.

Dating very young planetary surfaces from crater statistics: A review of issues and challenges

“…The interpretation of the model ages therefore may not be straightforward and may represent a steady state between production and removal of craters (Öpik , ), or a diminishing sequence of resurfacing processes, thereby providing a retention age regulated by the destruction rate instead of a surface formation age (Chapman and Jones ; Smith et al. ; Michael ; Fassett ; Kite and Mayer ).…”

“…Established approaches to dating planetary surfaces through the analysis of a superposed crater population rely on the technique of binning the measured crater diameters, and attempting to use the thus divided data to resolve the characteristic shape and density of the accumulating crater population (Hartmann ; Crater Analysis Techniques Working Group ; Neukum ). The method has seen numerous fruitful applications (see listing of predictive successes in recent review by Fassett ), but has always required caution when the number of observed craters is low.…”

“…; Le Feuvre and Wieczorek ; Hiesinger et al. ; Robbins ) as more recent image data have become available along with an improved understanding of impactor dynamics and asteroid populations (also see recent review by Fassett [] and references therein).…”

Amazonian fluvial outflow channels in Jovis Tholus region, Mars

“…The crater count‐derived crater retention ages for the channels vary from ~0.2 to ~0.5 Ga [ Ivanov , ] (Figure b). It is important to mention here that the ages obtained for the channels do not straightaway represent the exact time of the fluvial activity, whereas they reflect the crater retention age over the channels [ Fassett , ] or plausibly lava flow resurfacing activity, which is evident from Figure a. The inferred ages are the lower limit for channels, as it is possible that high erosional activity could have altered the surface and the true age can be much older [ Fassett , ].…”

On the importance of self-secondaries

“…This technique has been greatly improved with new advances in sample analyses methods, cratering mechanics, orbital dynamics, and multiwavelengths high-resolution datasets obtained by recent lunar and deep space explorations. A review on the establishment, usage and new advances of this technique is detailed by Fassett (2016). It is not overstated that this technique has built most of the time frames a b d c Fig.…”