A New Classification and Index Calibration of Lunar Impact Craters for Digital Terrain Analysis
- Авторы: Zhou Y.1,2, Yan L.1,2, Zhao H.1,2, Tu J.1,2
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Учреждения:
- School of Geography and Tourism
- National Demonstration Center for Experimental Geography Education
- Выпуск: Том 63, № 12 (2019)
- Страницы: 1069-1079
- Раздел: Article
- URL: https://journals.rcsi.science/1063-7729/article/view/193353
- DOI: https://doi.org/10.1134/S1063772919120084
- ID: 193353
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Аннотация
Impact craters are the most typical geomorphological structural unit on the lunar surface. The craters record the characteristics of the Moon’s spherical appearance and the history of its geological evolution, so they form a basis for studies on the lunar surface. At present, mainstream classification is mainly qualitative and focuses more on the morphological characteristics of individual craters rather than the characteristics of different combinations of structures between craters. This is not conducive to designing modern crater detection algorithms. In this study, 100 m resolution digital elevation model (DEM) data obtained with the laser height measurement method were used to analyze the crater morphology, and 1407 impact craters of different types were selected from the lunar surface. Then, the craters were divided into six types based on spatial combination structures between impact craters, degradation of the crater boundaries, and complexity of the crater cross-section: dispersed craters, connected craters, contained craters, dispersed craters with rim degradation, connected craters with rim degradation, and contained craters with rim degradation. Finally, four description indicators were selected to quantitatively describe craters and analyze the differences in crater morphology: the volume to represent the scale, the slope of the crater wall to represent the evolution degree, the posture ratio to represent the geometric characteristics, and the circularity to represent the complexity. The results demonstrated that the proposed classification can be used to effectively design an automatic detection algorithm and accurately depicts the basic morphological features of the craters.
Об авторах
Yi Zhou
School of Geography and Tourism; National Demonstration Center for Experimental Geography Education
Email: yanlong@snnu.edu.cn
Китай, Shaanxi Xi’an, 710062; Shaanxi Xi’an, 710062
Long Yan
School of Geography and Tourism; National Demonstration Center for Experimental Geography Education
Автор, ответственный за переписку.
Email: yanlong@snnu.edu.cn
Китай, Shaanxi Xi’an, 710062; Shaanxi Xi’an, 710062
Hao Zhao
School of Geography and Tourism; National Demonstration Center for Experimental Geography Education
Email: yanlong@snnu.edu.cn
Китай, Shaanxi Xi’an, 710062; Shaanxi Xi’an, 710062
Jie Tu
School of Geography and Tourism; National Demonstration Center for Experimental Geography Education
Email: yanlong@snnu.edu.cn
Китай, Shaanxi Xi’an, 710062; Shaanxi Xi’an, 710062
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