Abstract

The analysis of the impact crater size-frequency distribution (CSFD) is a well-established approach to the determination of the age of planetary surfaces. Classically, estimation of the CSFD is achieved by manual crater counting and size determination in spacecraft images, which, however, becomes very time-consuming for large surface areas and/or high image resolution. With increasing availability of high-resolution (nearly) global image mosaics of planetary surfaces, a variety of automated methods for the detection of craters based on image data and/or topographic data have been developed. In this contribution a template-based crater detection algorithm is used which analyses image data acquired under known illumination conditions. Its results are used to establish the CSFD for the examined area, which is then used to estimate the absolute model age of the surface. The detection threshold of the automatic crater detection algorithm is calibrated based on a region with available manually determined CSFD such that the age inferred from the manual crater counts corresponds to the age inferred from the automatic crater detection results. With this detection threshold, the automatic crater detection algorithm can be applied to a much larger surface region around the calibration area. The proposed age estimation method is demonstrated for a Kaguya Terrain Camera image mosaic of 7.4 m per pixel resolution of the floor region of the lunar crater Tsiolkovsky, which consists of dark and flat mare basalt and has an area of nearly 10,000 km<sup>2</sup>. The region used for calibration, for which manual crater counts are available, has an area of 100 km<sup>2</sup>. In order to obtain a spatially resolved age map, CSFDs and surface ages are computed for overlapping quadratic regions of about 4.4 x 4.4 km<sup>2</sup> size offset by a step width of 74 m. Our constructed surface age map of the floor of Tsiolkovsky shows age values of typically 3.2-3.3 Ga, while for small regions lower (down to 2.9 Ga) and higher (up to 3.6 Ga) age values can be observed. It is known that CSFD-derived absolute model ages can exhibit variations although the surface has a constant age. However, for four 10-20 km sized regions in the eastern part of the crater floor our map shows age values differing by several hundred Ma from the typical age of the crater floor, where the same regions are also discernible in Clementine UV/VIS color ratio image data probably due to compositional variations, such that the age differences of these four regions may be real.

Highlights

  • Impact crater counting is one of the most important tools for estimating the geologic age of a planetary surface, i.e. the period of time that has passed since the last resurfacing event

  • An image template matching based crater detection algorithm (CDA) has been applied to a Kaguya spacecraft image of the mare-like floor of the lunar crater Tsiolkovsky

  • The absolute model age (AMA) of the surface has been estimated based on the crater size-frequency distribution (CSFD) inferred from the detection results of the CDA

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Summary

INTRODUCTION

Impact crater counting is one of the most important tools for estimating the geologic age of a planetary surface, i.e. the period of time that has passed since the last resurfacing event. For planetary bodies without an atmosphere, the areal impact crater density increases with increasing surface age, i.e. densely cratered surface parts are usually older than surface parts with a low abundance of craters. The impact crater size-frequency distribution (CSFD), denoting the diameter-dependent areal density of impact craters for a given surface part, allows for an estimation of the so-called absolute model age (AMA) of the surface (Hartmann, 1999; Hartmann and Neukum, 2001; Michael and Neukum, 2010; Michael et al, 2012; Michael, 2013, 2014, 2015; Hiesinger et al, 2011). A surface age map is created based on the automatically obtained crater counts, resulting in a spatially resolved map of the AMA of the examined surface area

CRATER DETECTION ALGORITHMS
TEMPLATE-BASED AUTOMATIC CRATER DETECTION
THE REGION OF INTEREST
TSIOLKOVSKY AGE MAP
SUMMARY AND CONCLUSION
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