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### 基于DEM的月球雨海地区粗糙度研究

1. 南京师范大学虚拟地理环境教育部重点实验室,南京 210023
• 收稿日期:2013-11-15 修回日期:2014-03-15 出版日期:2014-08-20 发布日期:2014-08-10
• 作者简介:

作者简介:严艳梓(1991- ),女,福建莆田人,硕士,主要从事DEM数字地形分析研究。E-mail:yanyanzi519@gmail.com

• 基金资助:
国家自然科学基金项目(41171320);江苏省高校自然科学研究项目(13KJA170001)

### Lunar surface roughness of Mare Imbrium based on DEMs

Yanzi YAN(), Guoan TANG(), Liyang XIONG, Xuan FANG

1. Key Laboratory of Virtual Geographical Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, China
• Received:2013-11-15 Revised:2014-03-15 Online:2014-08-20 Published:2014-08-10

Abstract:

Surface roughness, as discussed in this paper, is defined as the topographic expression of surface on a kilometer scale. The lunar terrain reflects its geologic histories. Quantitative measurements of lunar surface roughness can be a powerful tool for interpreting spatial variations of lunar morphology, and contribute significantly to understanding surface formation and evolution process of the Moon. Previous work shows that surface roughness variations of the Moon often correspond to tectonic and volcanic process, while ignoring the possible effects of lithological conditions of geologic units and geologic ages of identical geologic unit on a moderate scale. Mare Imbrium has preserved important clues for lunar geologic histories from the Imbrian Period, a period of the Late Heavy Bombardment of the Moon, to the present day. Thus, analysis of lunar surface roughness of Mare Imbrium could be crucial to learn the Imbirum events and the profound effects on the subsequent and the present appearance of the Moon. Therefore, in this paper, Mare Imbrium is taken as the test area to analyse the possible influences of lithological conditions and geologic ages on distributions of lunar surface roughness respectively. DEMs, produced by three-line digital photogrammetric technology based on the imagery acquired by Chang'E-1 CCD camera, are applied to extract lunar surface roughness. A number of roughness parameters have been employed to quantify surface roughness. Here, three common and simple indicators, i.e. root-mean-square height (RMS height), root-mean-square deviation (RMS deviation) and Hurst exponent are used in investigating the signatures of surface roughness. Root-mean-square height is the standard deviation of heights about the mean, a description of vertical change of heights of sample points. RMS deviation is related to the structure function, measuring horizontal variation of heights. However, both of these two parameters exhibit dependence of scale. Hurst exponent not only describes the behavior of scale dependence, but also is a roughness parameter. Firstly, we use 30-km windows for surface roughness calculation, spaced 30 km apart. Then the results are overlapped with 1:5,000,000 geologic map of the test area to analyse the distribution of surface roughness grouped by different lithological conditions. Finally, to find out the variation of surface roughness with geologic ages, surface roughness is computed from each 20 east-west profiles with a length of 340 km, sampled in a region at latitudes 30°-45°N and longitudes 30°-20°W. The experimental results show: (1) The higher surface roughness are found in the highlands within crater walls and the rims of large basin, caused by tectonic uplift, while the lower one in dark plains is dominated by flow emplacement mechanisms of volcanic process. (2) Surface roughness can be closely related to lithological conditions of geologic units. There are five geologic units considered. Surfaces of dark materials consisting of lava flows are rough. Surfaces of circumbasin materials and materials of main-sequence craters comprising of impact breccia and/or impact molten rocks are roughest. Consequently, surface of distinctive materials and nondistinctive materials are rougher because of its compound of impact breccia and/or impact molten rocks and lava flows. (3) Surface roughness is higher where lava flows is older. It is indicated that young flows in south are smooth while successively older flows in the north increase slightly in roughness. But, such a trend is not universal. Young lava flows would become rougher than old flows when modified by impact craters. (4) Mare Iridum is roughest at the smallest scale and smoother at large scale. Topography is rougher at small scale with Hurst exponent ranging from 0.7 to 0.9 and a median value of 0.78, while smoother at large scale relative to small scale with Hurst exponent decreasing (even decreasing to 0).