Wöhler, ChristianAl-Tameemi, Atheer2019-01-232019-01-232018http://hdl.handle.net/2003/37886http://dx.doi.org/10.17877/DE290R-19873A fully automatic system of crater detection, fusion and age estimation is built and constructed to result in reliable results in comparison with manually long time manually process from experts and professionals. A new idea of an extension of crater detection algorithms (CDA) is the Age Estimation that relied basically on Crater frequency-size distribution (CSFD). The age estimation process for surfaces depends basically on the numbers of the craters detected on the Moon surface and the total area of that surface. It is examined how well a template matching method is suitable for determining the age of different lunar areas. Six artificially lit crater models are used to count the craters in the investigated areas using cross-correlation. A threshold value for the automatic crater detection algorithm has been calculated for each dataset in order to obtain the best reliable results followed by a fusion automatic process for duplicated detections. A new implementation of this approach is provided for estimating the surface age with the possibility of flexible threshold values needed for calibration and evaluation process. With these two above-mentioned automatic steps, this will result in a time reduction and reasonable crater detection and so far precise age values. An automatic age mapping process has been applied to use the optimal threshold value in larger homogenous areas for more efficiency and behavior study. For the purpose of testing accuracy and efficiency, a dataset from lunar nearside regions has been examined to find out if there is an ideal threshold value for the crater detection process so that the smallest possible errors in the surface ages - derived from manually detected craters – are found in comparison to values from the literature. For this purpose, the optimal threshold value is calculated in five areas of Mare Cognitum on the Moon and then use to determine the age of five other areas in Oceanus Procellarum. By subsequently comparing the calculated ages with those from the literature, the accuracy of the method is examined. An image-based CDA has been implemented on a different dataset of craters, the first group of the dataset is the LU60645GT catalogue that includes a large number of crater candidates with diameters between 0.7 km and 2.5 km and located in the large craters Alphonsus and Ptolemaeus. The second dataset is a different region on the Moon near the crater Hell Q that includes a limited number of small craters with very small diameters between 3 m and 70 m, while the third group of data contains a list of medium-sized craters (128 m-1000 m) on the morphologically homogeneous floor of the lunar crater Tsiolkovsky. In an advanced step, an automatic method of detection for secondary crater candidates on the lunar surface has been proposed. To assess the accuracy of the developed method, automatic crater counts were performed for the flat floor of the lunar farside crater Tsiolkovsky by applying the Voronoi tesselation based Secondary Candidate Detection (SCD) to the results of the template matching based crater detector. For a small are on the crater floor, the obtained age of 3.21 Ga is consistent with the age of 3.19 Ga determined by Pasckert et al. (2015). In the next step, the age estimation was expanded to the complete crater floor, resulting in a map of the surface age which is at least partially corrected for the influence of secondary craters.enPlanetary age estimationCrater detectionCDAAge mappingSecondary craters620TextMondMondkraterAstronomie