基于DEM的月表坡谱及空间差异性研究

发布时间：2018-04-19 02:41

本文选题：DEM + 坡谱　；参考：《南京师范大学》2015年硕士论文

【摘要】：月表地貌(lunar geomorphology)是月球表层内外营力长期综合作用的结果。系统地研究月表地貌形态特征、组合类型、空间分布及发育演化,对于揭示月表地貌的形成与发育机理有重要的科学意义。近年来,月表地貌特征的研究得到国内外学者的广泛关注,尤其是在撞击坑的提取及其形态的空间差异性研究方面已取得重大的科学成果,但是对月表宏观地貌形态特征及其空间差异性的研究仍显不足。作为一种利用微观地形指标来反映宏观地形特征的地形分析方法,基于DEM的坡谱分析已在黄土高原地貌的研究中成功实践并取得重要进展。本研究以多分辨率的月表DEM及USGS月球地质图(geologic map of the moon)为基础数据,以坡谱为切入点,研究月表宏观地貌形态的空间差异性特征。论文主要研究工作及结论包括：1)研究了月表坡谱稳定存在的基本地域条件,论证了坡谱在月表地貌研究的适宜性；2)运用空间统计采样理论研究了月表稳定坡谱的提取方法,该方法能较好地适应月表地貌类型多样且空间分布离散程度高的地貌特征；3)分析了月表坡谱的尺度效应,结果表明DEM分辨率变化范围在60 m-240m之间时,坡谱具有较好的稳定性,反映出在该空间尺度范围内月表地貌形态特征具有较强的自相似性；4)以坡度和地表粗糙度为核心参数,探索了月表坡谱的空间差异性特征。结果显示,月表坡谱具有明显的空间差异性规律,不同地貌类型的坡谱量化指标差异显著,从月海、高地、盆地到撞击坑,坡谱信息熵、面积-坡度积分值、面积-地表粗糙度积分值均逐渐增大,坡谱偏度依次减小,坡谱形态逐渐向正态分布变化；这些特征反映了月表地形起伏度从月海、高地、盆地到撞击坑逐渐增大,揭示了地貌成因对地形起伏空间格局的控制作用。5)选取19个坡谱因子,运用非监督分类方法,实现了月表地貌类型的自动分类,分类精度达70.3%。本研究是坡谱分析法在月表地貌研究的一次有益探索,为月表地貌研究提供了新的思路,有效地拓展了数字地形分析的应用地域。
[Abstract]:The lunar surface geomorphology is the result of the long-term comprehensive action of the inner and outer forces on the surface of the moon.It is of great scientific significance to systematically study the morphological features, assemblage types, spatial distribution and developmental evolution of the lunar surface geomorphology, which is of great scientific significance for revealing the formation and development mechanism of the lunar surface geomorphology.In recent years, the research on the geomorphological characteristics of the lunar surface has received extensive attention from scholars at home and abroad, especially in the extraction of impact craters and their spatial differences in morphology, which has made great scientific achievements.However, the study of the macroscopic geomorphologic features and their spatial differences on the moon surface is still insufficient.As a topographic analysis method based on microcosmic topographic index, slope spectrum analysis based on DEM has been successfully applied in the study of loess plateau geomorphology and important progress has been made.Based on the multi-resolution lunar surface DEM and USGS lunar geological map, the spatial difference of the macroscopic geomorphology of the lunar surface is studied by using the slope spectrum as the starting point and based on the data of USGS lunar map of the moon.The main research work and conclusions are as follows: (1) the basic regional conditions of the stability of the monthly slope spectrum are studied, and the suitability of the slope spectrum in the study of the monthly surface geomorphology is demonstrated. 2) the extraction method of the stable slope spectrum of the lunar surface is studied by using the spatial statistical sampling theory.This method can better adapt to the geomorphological features with various types of monthly surface landforms and high degree of spatial dispersion. The scale effect of the monthly slope spectrum is analyzed. The results show that the slope spectrum has good stability when the DEM resolution varies from 60 m to 240 m.The results show that there is a strong self-similarity in the geomorphologic features of the lunar surface within this spatial scale. (4) taking slope and surface roughness as the core parameters, the spatial differences of the slope spectrum of the lunar surface are explored.The results show that the slope spectrum of lunar surface has obvious spatial difference law, and the quantitative indexes of slope spectrum of different geomorphological types are significant, ranging from lunar sea, highland, basin to impact crater, slope spectrum information entropy, area-slope integral value.The integral value of area-surface roughness increases gradually, the slope spectrum bias decreases in turn, and the slope spectrum forms gradually change to normal distribution, which reflects that the relief degree of the lunar surface topography increases from the lunar sea, the highland, the basin to the impact crater.This paper reveals the controlling effect of geomorphologic origin on the spatial pattern of topographic undulation. 5) selecting 19 slope spectrum factors and using unsupervised classification method, the automatic classification of monthly topographic types is realized, and the classification accuracy is up to 70.3%.This study is a useful exploration of slope spectrum analysis in the study of monthly topographic features, which provides a new way of thinking for the study of monthly topographic features and effectively expands the application area of digital topographic analysis.
【学位授予单位】：南京师范大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：P184

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