Automatic extraction of multiple morphological parameters of lunar impact craters

Abstract

Impact craters are geomorphological features widely distributed on the lunar surface. Their morphological parameters are crucial for studying the reasons for their formation, the thickness of the lunar regolith at the impact site and the age of the impact crater. However, current research on the extraction of multiple morphological parameters from a large number of impact craters within extensive geographical regions faces several challenges, including issues related to coordinate offsets in heterogeneous data, insufficient interpretation of impact crater profile morphology and incomplete extraction of morphological parameters. To address the aforementioned challenges, this paper proposes an automatic extraction method of morphological parameters based on the digital elevation model (DEM) and impact crater database. It involves the correction of heterogeneous data coordinate offset, simulation of impact crater profile morphology and various impact crater morphological parameter automatic extraction. And the method is designed to handle large numbers of impact craters in a wide range of areas. This makes it particularly useful for studies involving regional‐scale impact crater analysis. Experiments were carried out in geological units of different ages and we analysed the accuracy of this method. The analysis results show that: first, the proposed method has a relatively effective impact crater centre position offset correction. Second, the impact crater profile shape fitting result is relatively accurate. The R‐squared value (R2) is distributed from 0.97 to 1, and the mean absolute percentage error (MAPE) is between 0.032% and 0.568%, which reflects high goodness of fit. Finally, the eight morphological parameters automatically extracted using this method, such as depth, depth–diameter ratio, and internal and external slope, are basically consistent with those extracted manually. By comparing the proposed method with a similar approach, the results demonstrate that it is effective and can provide data support for relevant lunar surface research.