ABSTRACT
Ages of planetary surfaces are typically obtained by manually determining the impact crater size-frequency distribution (CSFD) in spacecraft imagery, which is a very complicated and time-consuming procedure. In this chapter, a template-based crater detection algorithm (CDA) is used to analyze image data under known illumination conditions. For this purpose, artificially illuminated crater templates are used to detect and count craters and their diameters in the areas under investigation. Firstly, we investigate how well our CDA is suitable to determine the absolute model age (AMA) of different lunar regions. The sensitivity of the CDA is calibrated based on five different regions in Mare Cognitum on the Moon such that the age inferred from the manual CSFD measurements corresponds to the age inferred from the CDA results. The obtained detection threshold is used to apply our CDA to another five regions in Oceanus Procellarum. It is shown that the automatic age estimation yields AMA values that are consistent with values obtained by manual CSFD measurements. Then the image-based CDA is applied to the floor region of the lunar farside crater Tsiolkovsky. The obtained CSFD is then used to estimate the AMA of the surface. The detection threshold is calibrated based on a 100 km² test area for which the CSFD has been determined by manual CSFD measurements in a previous study. Furthermore, CSFDs and AMAs are computed for overlapping quadratic regions covering the complete floor of Tsiolkovsky. This results in a spatially resolved age map showing AMAs of typically 3.2–3.3 Ga, while for small regions lower and higher AMAs are found. It is well known that the CSFD may be affected by seondary craters. Hence, we present a method to refine our detection results by applying a secondary candidate detection (SCD) algorithm relying on Voronoi tessellation of the spatial crater distribution which searches for clusters of craters. The detected clusters are assumed to result from the presence of secondary craters which are then removed from the CSFD, where it was favorable to apply the SCD algorithm separately to each diameter bin of the CSFD histogram. In comparison to the original age map, the age map obtained after removal of secondary candidates has a more homogeneous appearance and does not exhibit regions of spuriously high age resulting from contamination by secondary craters.
This chapter has mostly been adopted and/or adapted from the works of Salih et al. (2016), Salih, Lompart et al. (2017), Salih, Schulte et al. (2017).
