Back to results list
Show full item record
Please use this identifier to cite or link to this item:
|Title:||Spatial distribution and morphological characteristics of lunar craters based on reliable crater detection from lunar imagery and DEM||Authors:||Wang, Yiran||Degree:||Ph.D.||Issue Date:||2020||Abstract:||Impact craters are the predominant geological features on the lunar surface and can be studied to infer the ages of the Moon's surfaces, the generation processes of the geological units, and the sequences of its geological events. Due to limitations in the spatial resolution of the available data, previous studies on lunar craters have typically been focused on large craters, i.e., craters with diameters of a few kilometres to dozens of kilometres. In the last decade, images or digital elevation models (DEMs) of the Moon with higher resolution on a global scale have been powered by regularly collected stereographic high-resolution images or laser altimetry data onboard lunar-orbiting satellites, such as the Lunar Reconnaissance Orbiter (LRO), the Selenological and Engineering Explorer (SELENE), and Chang'E-2. These higher-resolution remote-sensing datasets offer new opportunities for the investigation of relatively small impact craters and to thus provide more accurate lunar geological information. Lunar crater-related research is dependent on crater records, which are usually stored in the form of crater catalogues. The generation of a lunar crater catalogue requires more automated methods of crater detection, as it involves a large number of dense datasets. To this end, this research first focused on two approaches to crater detection and an approach for the automatic extraction of crater morphological information. A machine learning approach for crater detection based on DEMs was designed for crater detection on a global scale, based on the use of the histogram of oriented gradients (HOG) feature descriptor, a support vector machine (SVM) and multiscale detection. An active learning approach for crater detection based on lunar imagery and DEM was designed for detecting craters on local scales. The machine learning strategies of Haar-like features, adaptive boosting, and cascades were adopted in this approach. This approach was distinct from conventional machine learning methods in that it actively asked for annotations for the 2D features derived from imagery with inputs from 3D features derived from the DEMs; this active learning process thus enabled the more automated collection of good numbers of high-quality training samples. The approach for the extraction of crater morphological information was based on Gaussian fitting. It was able to automatically calculate crater depth, wall slope, bottom width, rim height, central peak height and widths through crater profiles. Evaluation experiments confirmed the efficacy of these proposed approaches. In the past, various efforts have been dedicated to generating global lunar crater catalogues. All published global catalogues, however, either contain only relatively large craters or lack 3D morphological information. An improved global catalogue of lunar craters, LU1319381, has been generated based on the developed approaches for crater detection and morphological information extraction, and extensive manual checking efforts using previously published catalogues (Head et al., 2010; Robbins, 2019) as a basis for ground-truthing to improve the correctness and completeness of the detection results. This new catalogue contains entries for 1,319,381 craters ≥1 km in diameter, with detailed 3D morphological information such as crater depth, wall slope, bottom width, rim height, central peak height and width provided for each crater. Based on the new global catalogue of lunar craters, global analyses of spatial distribution and morphological characteristics of craters have been conducted, such as analyses of crater densities, saturation equilibrium and depth-to-diameter ratios. The analyses showed that the global crater density of large craters (>20 km) was in good agreement with previous studies. The global crater density of relatively large craters (1-5 km) showed better spatial resolution and better matches with the boundaries of lunar mare and highlands. A global analysis of crater depth-to-diameter ratios revealed that small craters (~1-4 km) on the lunar mare have larger depth-to-diameter ratios than those on the highlands. Besides, it was found that the transition from simple to complex craters on the highlands occurred at a diameter of ~11-22 km, which was in general agreement with previous research. However, a novel finding was that the transition on mare occurred at a smaller diameter of ~8-16 km.
In addition to performing a global analysis of craters, a local region of particular interest on the lunar surface, the Orientale Basin, was also selected for systematic investigation, which comprised an analysis of the distribution and population characteristics of impact craters in and around the Basin. The Orientale Basin is the youngest and one of the most-studied large multi-ringed basins on the Moon. It has been regarded as the 'archetype' basin for the process of basin formation with highly preserved impact craters. An updated crater catalogue containing entries for craters of diameter ≥1 km in the Orientale Basin and its surrounding area was generated based on the developed approaches for crater detection and morphological information extraction, thus enabling an investigation of the crater densities and depth-to-diameter ratios in and around the Orientale Basin. The inclusion of small craters facilitated the creation of a crater density map with higher resolution. The surface age of the Orientale Basin was estimated from the size-frequency distribution (SFD) using the new crater catalogue, showing the age of 3.75 Ga using the production function of Neukum et al. (2001), which was in good agreement with previous studies. Finally, distribution patterns of secondary craters around the Orientale Basin were investigated, and these indicated that the Orientale Basin might have been generated by an oblique impact with a downrange direction of approximately 235°-260° and an offset strength towards the direction of approximately 305°-350°. The research and developments presented in this dissertation are of significance and utility for all scientific research related to lunar craters. The new global crater catalogue that has been generated is more complete than any previously published efforts. It also provides 3D morphological information of craters, which has never been achieved before. Analyses of craters on both global and local scales based on this new global crater catalogue have afforded up-to-date and novel insights into key lunar geological aspects such as impact cratering, crater distribution and saturation, and crater chronology. The developed approaches and research outputs will inform and aid similar research of craters on other natural celestial bodies, such as the planets Mars and Mercury.
Imaging systems in astronomy -- Data processing
Hong Kong Polytechnic University -- Dissertations
|Pages:||xx, 143 pages : color illustrations|
|Appears in Collections:||Thesis|
View full-text via https://theses.lib.polyu.edu.hk/handle/200/10720
Citations as of May 15, 2022
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.