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地球科学进展, 2018, 33(9): 885-897
doi: 10.11867/j.issn.1001-8166.2018.09.0885
全月球形貌类型分类方法初探
A Preliminary Study of Classification Method on Lunar Topography and Landforms
程维明1,2,, 刘樯漪1,2, 王娇3, 高文信1,4, 刘建忠5
1.中国科学院地理科学与资源研究所 资源与环境信息系统国家重点实验室,北京 100101
2. 中国科学院大学,北京 100049
3.中国地质大学信息工程学院,北京 100083
4.兰州理工大学土木工程学院,甘肃 兰州 730050
5.中国科学院地球化学研究所,贵州 贵阳 550081
Cheng Weiming1,2,, Liu Qiangyi1,2, Wang Jiao3, Gao Wenxin1,4, Liu Jianzhong5
1.State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
3.School of Information Engineering, China University of Geosciences, Beijing 100083, China
4.School of Civil Engineering, Lanzhou University of Technology,Lanzhou 730050, China
5.Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China
 引用本文:
程维明, 刘樯漪, 王娇, 高文信, 刘建忠. 全月球形貌类型分类方法初探[J]. 地球科学进展, 2018, 33(9): 885-897, doi:10.11867/j.issn.1001-8166.2018.09.0885
Cheng Weiming, Liu Qiangyi, Wang Jiao, Gao Wenxin, Liu Jianzhong. A Preliminary Study of Classification Method on Lunar Topography and Landforms[J]. Advances in Earth Science, 2018, 33(9): 885-897, doi:10.11867/j.issn.1001-8166.2018.09.0885

摘要:

月球表面形貌科学研究是月球探测最基础的内容。月球形貌类型单元的划分、月貌图的编研是绕月探测工程遴选的4项科学目标之一。首先回顾了不同研究者提出的月球表面形貌类型,论述了月球形貌类型的划分方法及进展,分析了20世纪70年代美国地质调查局编制全月球1∶ 500万地质图以及中国新一代1∶ 250万地质图的形态及年代的类型划分依据等。考虑到月球表面形貌的现状特征、受宏观营力格局及作用方式、形态变异及组合特征等,提出了基于形态和年代两大类特征相结合全月球形貌类型的矩阵式多级分类方法。年代可分为哥白尼纪、爱拉托逊纪、雨海纪、前雨海纪以及两者之间的过渡年代等七大类。全月球形貌类型中,按照宏观形态及营力作用方式,将第一级划分为月海、盆地、月陆和撞击坑四大类。第二级中,按照大类的形态差异性,可将盆地分为盆底平原和环盆地山丘;月海分为月海平原和月海穹丘;月陆分为月陆平原、月陆丘陵和月陆高原;撞击坑按照形态和规模分为特大型撞击坑环形山、特大型撞击平原、次级形成小撞击坑、撞击坑链、带辐射纹撞击坑、不规则和边缘模糊坑、未分形态撞击坑等类型。根据坡面和物质差异,可细化出三级甚至四级形态类型。以H010幅为案例,对2种指标和组合形貌类型进行了制图试验。这将对全月球形貌类型的划分和制图具有一定的指导作用。

关键词: 月球形貌 ; 形貌特征 ; 地质年代 ; 地貌分类 ; 分类方法

Abstract:

Lunar topography and landform, resulting from endogenous and exogenous geophysical processes of various spatial and temporal scales, carry information of these processes and target properties. Geoscientists use morphometric analysis at different scales to study lunar topography, which is one of the four scientific objectives of China's lunar exploration project. This article first reviewed the lunar topographic types from different researchers, analyzed classifying method and progress, discussed geological mapping method of 1∶ 5 000 000 complied by United States Geological Survey in the 1970s. In consideration of the present situation of the lunar surface morphological characteristics, the pattern of macroscopic forcing, morphologic variation and combination characteristics and function way, etc., a matrix combining multi-stage classification method was put forward based on the characteristics of the topography and geologic age, which included 7 geologic ages and 14 morphologic classes. Geological ages can be divided into Copernican System (C), Copernican-Eartosthenian System (CE), Eartosthenian System (E), Eartosthenian-Imbrian System (EI), Imbrian System (I), Imbrian-PreImbrian System (IpI) and Pre-Imbrian System (pI). As to topographic types, the first class can be divided into lunar mare, lunar basin, lunar terra and lunar crater. As to their second class according to morphological differences, the lunar basin can be divided into basin plain and circum-basin, and lunar mare can be divided into mare plain and mare dome; lunar terra can be divided into terra plain, plateau and hill, and craters can be divided into main sequence crater, crater plain, secondary crater, crater chains and clusters, rayed craters, irregular crater and undivided crater. Thus, 46 subclasses including geologic and morphologic features were obtained in this classification system. The test mapping method was addressed in Sheet H010, which shows the combination classification method is reasonable.

Key words: Lunar topography ; Morphological features ; Geologic ages ; Geomorphologic classification ; Classification approach.
1 引 言

月球作为地球的唯一卫星,是人类进行深空探测的首要天体,其表面形态特征是人类进行直接观测研究的最佳窗口[1]。不同于地球表面复杂的大气环境及频繁的地质活动,月球几乎没有大气层和液态水,几乎没有受到较近年代地质活动的影响[1]。对月球表面形貌塑造的外营力主要体现在月球早期的岩浆活动、外来天体的撞击及昼夜和阴阳面的温差、太阳风、宇宙射线等,这些作用中除外来天体的撞击外,其他对月球表面地貌的破坏作用相对较弱[1]。因此,对月球形貌特征进行研究,可了解月球的状态、结构和组成,为探究月球起源和演化历史等科学问题提供直接、可靠的证据,是月球探索过程中必不可少的基础性工作[2,3]

通过美国克莱门汀号(Clementine)[4,5]和近年来各国在月球探测中获得的海量遥感数据[6,7],国内外学者从不同方面开展对月球形貌的研究,主要集中在以下几方面:通过月球地图和地图集的编制表达月球表面形貌[6,7,8,9,10];基于照片、遥感影像、雷达数据等数据类型和不同方法构建月球地形模型[11,12,13],模拟月面环境;基于不同尺度、数据源和方法提取月球基本形貌单元[14,15,16,17]

从19世纪初就开始从不同角度和层次对月球形貌进行研究[18],但月球形貌类型的划分并没有引起诸多学者的关注。同时,相对于全月球尺度的形貌特征分析,更多的学者倾向于研究典型月貌类型,如对月球撞击坑依据形态特征进行系统分类[19]等。尽管对于全月球形貌类型的相关研究不算完善,但前人的工作为后续研究奠定了基础,并且随着日益成熟的探月技术带回优质有效的月球数据,为全月球形貌类型的划分及数字月球形貌图编研工作的大量开展提供了契机。本文先分析了全月球形貌类型的研究进展,在此基础上对比分析月球形貌类型划分方法的历史和现状,最后提出全月球形貌类型的多级分类指标、分类方法和分类体系,并以H010幅为案例,进行月球形貌类型的制图试验,以期加深对月球形貌过程的认识,服务于月球的演化过程及机理研究。

2 月球形貌特征的分类及提取方法
2.1 月球形貌特征的分类

月球的地貌特征包括形态特征、地质特征、物质特征和年龄特征等多个方面,下面将主要讨论形态和地质特征。

2.1.1 基于形态特征的分类

月球形貌学研究月球表面的起伏形态、分布规律、物质结构、发展历史和开发利用,而划分月球形貌类型是月球形貌研究的基础工作[1,2]。月球形貌类型远不如地球的地貌类型多变复杂,认为月球不是完美光滑的想法可以追溯到大约公元前450年,当时Democritus相信月球上有“高大的山脉和空旷的山谷”,直到15世纪末人们才开始认真研究月球表面[20,21,22,23]。1645年荷兰天文学家Michael Florent van Langren从望远镜中观察月球表面特征,绘制了被认为是首幅真实的月球图,认为月球表面有月海、陨石坑及山峰和山脉等地貌类型[20,21,22,23]。1651年Giambattista Riccioli推出的现代月球命名体系中还命名了月洋、月湖、月沼、月湾等与“水”有关的地貌类型[20,21,22,23]。1779年Johann Schröter开始对月球特征进行了细致的观察和测量[20,21,22,23]。1791年Johann Hieronymus Schröter发表了题为《对月球表面更精确了解的月球地形图》的有关月球地形的早期研究,首次提出了可见月球“反射率”的概念[13,14,15,16]。1840年Draper使用一架直径约12.7 cm的反射望远镜拍摄第一张月球银版相片将摄影引入到天文界,1959年前苏联的月球3号发回了首张月球背面的照片,1978年美国宇航局公布了月球地形正射影像图[20,21,22,23],这些观测、研究成果让全世界看到月球最显著的外观是明暗对比区域及坑坑洼洼的凹地,更明亮的部分是月球高地,也被称作月陆,更暗的区域被称作月海,凹地则是撞击坑,这三大地貌单元构成了月球形貌的基本类型[20,21,22,23]。1982年Andersson和Whitaker按照撞击坑、非撞击坑和其他地貌特征三大类型对月球形貌进行分类[20,21,22,23]。之后国际天文联合会(International Astronomical Union,IAU)在1982年分类的基础上将月球形貌类型具体划分为撞击坑、月海和月陆3个一级地貌类型,月洋、月湖、月沼、月湾、月岬、山地、穹丘、皱脊、月谷、陡坡和月溪等二级地貌类型[24]。2013年程维明等[2]和周增坡等[25]借助于遥感影像解译标志特征,将月貌典型类型进行了分类,主要包括月海、月陆、台地、丘陵、山地、 撞击坑平原、环形山、撞击坑链、月溪或月谷和月岭等类型(表1)。撞击坑有诸多分类方案[2,3],王娇等[26]在对比各种方案后,提出撞击坑形态和规模相结合的比对指标,将全月球撞击坑分为月海残留型、特大复杂型、大环状平原型、中等凹坑平原型、小规模碗型和微状酒窝型六大类,并发现不同类型的撞击坑在月球表面的分布存在很大的差异。

表1

不同时期研究者提出的月球表面形貌类型对比

Table 1

Different types of lunar landform classifications

2.1.2 基于地质特征的分类

20世纪70年代,美国地质调查局曾编制了1∶ 500万全月球地质图[27,28,29,30,31,32],按照编制的任务分工和完成的先后顺序,全月球共分为6块,即近月面、东面、西面、中远面、北面和南面。对比6块地质图信息,可以发现,地质信息包括了3层内容:地质年代、地质单元物质、地质单元的地形地貌特征。对于物质特征,综合地质数据信息,可以概括为暗物质、盆地物质、月陆的平原—高原和丘陵物质、撞击坑物质四大类。在年代和物质的控制下,可划分出不同年代和物质背景下的地形地貌单元,月海地貌类型可划分为月海平原、月海丘陵、月海高原和月海穹丘等;大型盆地地貌类型可分为盆底平原和环盆地山丘等;月陆地貌类型可分为月陆丘陵、月陆平原、月陆高原和月陆山脉等;撞击坑按照规模和形态可分为主撞击坑、撞击坑链、不规则撞击坑和未分撞击坑等(表2)。可见,该地质信息的表述采用了矩阵式结构,按照物质、年代和地貌类型三者进行组合。

表2

美国月球地质图中涵盖的月球形貌类型特征[27,28,29,30,31,32]

Table 2

Landform types included by geologic maps of the moon compiled by USGS[27,28,29,30,31,32]

丁孝忠等[33]和陈建平等[34]综合对撞击坑和溅射堆积物的分析,依据月坑的形态特征、填充物质的多少和保留程度等,将月球撞击坑划分出7种类型11个亚类,包括:碗型月坑、中央峰月坑、多环月坑、辐射型月坑、填充月坑、残缺月坑和残余月坑。其中,中央峰月坑又可分为回落堆积型中央峰月坑和陨石残体型中央峰月坑;填充月坑可被分为全填充月坑、满填充月坑、半填充月坑、无填充月坑。

在新一轮月球地质图的编研中,欧阳自远等[35]从月球表面构造域和深部构造域角度进行表达,在2种构造域中按照形态分为环形构造和线性构造,并在此基础上,按照成因进一步划分[35,36]。其中对于月球表面构造域的研究即是对于月貌类型的划分。根据构造成因不同,月球表面环形构造域可进一步可划分为撞击坑(含盆地)、冷凝环和火山口3类,而月球表面线形构造域则可划分为月岭、断裂、坑链、地堑、月溪、月谷和其他共7个类别。对于撞击坑而言,又可进一步划分出中央峰、坑底、坑壁、坑缘、坑唇、辐射纹等。这种分类方式从地质角度出发,包含了构造成因、形态等多种因素。

2.2 月球形貌类型识别方法

2.2.1 地形因子计算及识别

Florinsky[37]基于克莱门汀号重力和地形数据在全月球尺度上计算了15个地形因子,其中平面曲率图中能反映出撞击坑所在区域,但是不能分辨出撞击坑的边界,剖面曲率图上能识别出澄海和危海的边界,集水区分布图上能识别出东海和云海的边界,其余12个地形因子在月球形貌类型分类上作用不明显。

除了传统的地形因子,近年来有学者用粗糙度来解译月球表面地貌,但地表粗糙度实质上也是用地形因子表征的一个指数,Rosenburg 等[38]使用月球侦察轨道器从2009年9月17日至2010年3月9日获取的3 180条轨迹数据,计算和分析表面坡度和粗糙度的各种参数,以区分月陆和月貌的差异,具体参数分别是平均坡度、平均坡度差和Hurst指数(一种和分形相关的指数)。研究发现,月陆和月海对比有截然不同的粗糙度,但不同空间位置的月海粗糙度几乎没有差别,月陆本身也表现出这样的特点。月陆的Hurst指数为0.95接近于1,被称为自相似地形,月海的Hurst指数为0.76,这说明月陆在研究尺度不断变大时,其地形粗糙度维持在一个稳定的水平,而月海在大尺度上的地形特征会被平滑。粗糙度常用在月球表面形貌特征的识别和定量表达上,要结合相应的提取方法才能完成地貌类型的划分工作。奚晓旭等[39]在月球虹湾地区采用月球轨道飞行器激光测高仪获取的高程数据,利用粗糙度地形指数包括:均方根高程、均方根偏差、均方根坡度和Hurst指数对月球表面虹湾地区的地形地貌进行了解译,结果表明虹湾地区月球表面起伏度小,地形地貌样式单一,把区域尺度与全月尺度上的粗糙度对比可以研究区域特殊的历史演化过程。

王琛智等[40]认为数字高程模型(Digital Elevation Model,DEM)结合其派生地形因子建立指标体系的方法在宏观尺度对月海和月陆进行识别和提取效果理想,在区域尺度上可扩展性差,不同地区难以共用同一套地形因子构建指标体系,而且指标体系中各因子权重设置具有较大的主观性。其在区域尺度上从月球表面地形纹理特征的角度出发,利用灰度共生矩阵模型,以DEM数据为基础,量化表达地形纹理特征的指标,筛选出能有效区分2类月球表面形貌单元的特征向量,然后选用离差平方和作为识别器自动识别月海和月陆,整体识别率达到85.7%,在实验区取得了较好的识别结果。

此外,Bue[41]利用DEM 获得的地形指标,采用非监督分类在区域尺度上对火星地貌进行自动分类的方法对月球形貌类型划分。针对火星表面撞击坑广泛分布的特殊地形,先采用淹没算法处理高程数据,随后选择高程、坡度、集水区、淹没高程、淹没坡度和淹没集水区6个地形因子输入到自组织神经网络模型(隶属于非监督分类)中,将带有地形信息的所有像素划分为相互排斥或相似的地貌单元,相同地貌类型像素具有最大的相似性,最小的差异性,最终在实验区Terra Cimmeria区划分出5个一级地貌类型,19个二级类型。

2.2.2 遥感与地形综合识别

周增坡等[25]基于嫦娥一号全月高程及影像数据,在月球标准分幅H010区域,选择高程、坡度、起伏度及影像灰度值4个指标先对指标归一化处理,然后应用最大似然法进行月海和月球高地的自动提取,这4个指标从不同侧面刻画了月海和月球高地地形及物质反照率的差异,提取结果与美国地质调查局出版的全月球地质数据进行一致性分析,得到Kappa系数为0.78。

李婧等[42]、李珂等[43]和王楠[44]以嫦娥一号影像数据和LOLA(Lunar Orbiter Laser Altimeter)激光高度计数据和LRO (Lunar Reconnaissance Orbiter)的宽视角影像数据为基础,分别以澄海、马里纳斯坑和静海为研究区域,选择地形曲率为提取地表线性特征的地形因子,并利用不同滑动窗口大小和阈值进行线性构自动提取月岭和月溪,此方法为月球表面线性构造解译提供重要参考,提高了线性构造解译时效性和精度。月球极地和背面的线性特征也被分析和挖掘[45]

撞击坑的识别和提取研究非常多,包括人工识别、自动识别[41,42,43,44,45,46,47,48,49,50]等。近年来,随着海量影像和DEM数据的不断获取,计算机技术的不断发展,对撞击坑的提取方法不断创新。基于图像的撞击坑自动分类大体上可以分为以下三大类:边缘检测、霍夫变换和机器学习。对于边缘检测类:包括基于某种固定的局部算法[51,52],如传统的基于模板和梯度的算法、Robert算子、Sobel算子、拉普拉斯算子、Prewitt算子和Cany算子等;以能量最小化为准则的全局检测算法,其特点是运用严格的数学方法进行分析,得到最优的一维值代价函数为依据进行边缘提取,如神经网络分析法等[53];近年来发展起来的以数学形态学、小波变换、分形理论等为代表的图像边缘检测方法,尤其是基于多结构元素、多尺度特征的形态学边缘检测的方法[54,55];基于模版匹配的方法[56,57];基于椭圆拟合的方法[58,59];基于AI技术的方法[60]。霍夫变换类:Honda等[61]提出基于组合Hough变换的撞击坑检测;Sawabe等[62]对月球遥感影像数据进行了边缘检测、二值化、边缘细化、连接、坑心确定等处理,利用模糊霍夫变换识别撞击坑。机器学习类:Burl等[63]通过借鉴机器学习和计算机视觉的理论,建立了一套可训练的算法来提取和识别不同尺寸的撞击坑。

基于DEM的撞击坑自动分类主要是利用地形信息对撞击坑识别、分类,Wan等[64]采用DEM填洼、面向对象分类、DEM填洼的面向对象分类3种自动提取方法在DEM上进行撞击坑提取试验,表明填洼—面向对象的方法具有更高的提取精度;Salamuni c'car 等[65,66]利用DEM数据,运用霍夫变换、特征匹配面向对象等方法对火星和月球上的撞击坑进行了自动提取,得到了一系列撞击坑数据目录;Luo等[67]也利用嫦娥一号的DEM数据获得的地形指标,获得了全月球直径大于10 km的撞击坑边界;Di等[68]基于地形数据,利用机器学习方法提取撞击坑。Bue等[69]不仅考虑到了坡度信息,还加入了纹理和剖面曲率信息,以提高撞击坑识别的精度;Hawke等[70]采用形态和纹理特征对亚公里级别的撞击坑进行识别。

融合遥感影像与DEM的识别方法点在于找到一种既适应于基于遥感影像的又适应于基于DEM的识别方法[46,47,48,49,50]。Salamuni c'car等[71]先用遥感影像重建DEM,然后基于重建的DEM选择以霍夫变换为核心的识别方法提取撞击坑,在特定的区域内,被正确识别的撞击坑数量有显著增加;Wang等[72]用嫦娥一号遥感影像重建DEM以获得相同分辨率的本底数据,然后再重建的DEM上提取坡度因子和剖面曲率因子,加权融合后利用撞击坑边缘点突变性识别撞击坑的边界,建立了直径大于500 m的全月球撞击坑数据目录;罗中飞等[73]先利用太阳光照条件下撞击坑在影像中的特征,通过条件匹配实现撞击坑的自动提取然后在DEM中,利用撞击坑坑壁点坡向值的连续性,对影像中误提取的撞击坑进行剔除,最后在DEM中通过坑底点云所占比例以及剖面线特征识别撞击坑的类型。具有辐射纹的撞击坑因明显的专家作用遗留的痕迹,为提取撞击坑提供了途径[74,75]

2.3.3 人工判读识别

对月球典型形貌特征(如月溪)的提取研究已有很多成果[76]。近年来,李力等[77]基于多源数据(嫦娥一号影像、月球轨道飞行器激光测高仪获取的DEM、月球勘测轨道器相机图像和Clementine紫外/可见光多光谱图像)对月球Aristarchus 地区弯曲月溪的形貌特征从影像特征、形貌特征(长度、宽度、深度、区域坡度和月溪剖面)和物质组成3个方面进行解译分析,研究结果支持弯曲月溪的玄武岩熔岩流热侵蚀成因,表明研究区内的弯曲月溪具有相同的物源特征,月球表面坡度是控制月溪的主要因素。

3 全月球形貌类型的分类新方案
3.1 分类原则

鉴于月球地质演化过程、表面现状形貌特征以及现状营力作用方式[1,2,19,27~32,78],在综合借鉴地球地貌类型分类时遵循的主导性形态成因分类原则的基础上[79],初步提出适用于月球形貌类型的形态+年代相结合的分类原则:

(1)主导因素原则。和地球表面不同,月球表面现在未发现大气和水等外力作用,改变表面形貌的外力主要是太阳风及外来物体的撞击。各种营力作用在月球表面,形成现今的月貌形态,同时也影响着月球表面物质的分布。因此,月球表面形貌类型分类的主导因素应该为表面形态特征,它记录了地质历史时期的各种营力在月球表面的作用方式及遗留痕迹。将地质年代作为辅助分类的指标[1,2,19,27~32,78]

(2)逻辑性原则。跟地球地貌分类相一致,月球形貌分类应该遵循逻辑性原则,对于月球的形貌类型,以反映宏观特征的月海、月陆、撞击坑及盆地作为四大基本形态类型[1,2,19,27~32,78],再按照外貌形态变化进行逐级细化,以满足先群体后个体、先综合后单一、先大后小、先主后次等逻辑分类次序。

(3)定量化原则。基于精细DEM和遥感影像等海量数据源,对月球形貌类型的指标可实现指标的定量化,如月海区域玄武岩含量、月陆区域月岩亮度值差异等,撞击坑的大小规模、形状指数、坑深比等,实现月球地貌类型指标的定量化[79]

(4)完备性原则。分类方法要求包含多种要素,并能不断扩充分类指标。除了反映月球表面形貌的形态差异性、地质年龄,还可以根据研究需要增加其他指标,以实现分类体系的完备性[79]

3.2 分类方法

月貌分类体系中,根据涵盖的地理意义及内涵,指标可以分为不同的类别,如形态指标、年代指标、物质指标等。而在每类指标内部,根据划分的详细程度,指标又可以分为不同等级,如一级形态、二级形态等。因此,月貌分类体系的构建实质上可以认为是类内指标的层级划分以及类间指标的组合。本文类内指标的层级划分使用等级分类方法,类间指标组合采用矩阵式组合方法;采用等级分类方法对每类指标进行等级划分后再以矩阵式组合方法将各类指标组合起来,构成完整的分类体系。

(1)等级分类。在上述分类原则的指导下,月球形貌类型的分类采用等级分类方法,即按照先群体后个体、先综合后单一等逻辑分类次序,将月球表面形貌类型划分出一级形态、二级形态等不同等级,等级之间类型应存在包含关系,每种等级的形貌类型只能出现在某一特定类型中,避免等级类型的遗漏和重复。

(2)矩阵式组合方法。为能充分体现月球形貌类型分类的完备性和逻辑性,拟采用矩阵式组合方法作为多类指标的组合方法,以实现不同类别指标的组合,便于形貌类型等级之间的管理编码[79]

3.3 分类指标

(1)地质年代。和地球不同,月球表面无大气覆盖,除小行星的撞击作用和太阳风等作用外,地质历史时形成的地貌特征能较好地保存下来,因此地质年代可清晰地反映出地貌特征形式的过程及变化[1,2,19,27~32,78]。根据20世纪70年代美国编制地质图反映的地质年代特征,在6个分块中,近正面块的地质年代分为哥白尼纪、爱拉拖逊纪、雨海纪和前雨海纪4个时段。而其他5块分为哥白尼纪、爱拉拖逊纪、雨海纪、酒海纪和前酒海纪5个时段[27,28,29,30,31,32],为了便于比较,将酒海纪与前酒海纪合并起来,并将其统称为前雨海纪。故该方案中的地质年代可划分为哥白尼纪、爱拉拖逊纪、雨海纪、前雨海纪及其两者的过渡年代,共7个年代。

(2)形态指标。根据表面形态特征,可将月球形貌类型按等级先划分成月海、盆地、月陆和撞击坑4个一级类[1,2,27~32,80,81]。由于改变表面形貌的外力主要是太阳风及外来物体的撞击,而月球表面物质差异同样能够反映出其所在的地貌单元的形成条件,因而由形态指标划分而成的月球形貌的宏观形态与由物质指标划分得到的具有一定的相似性。在实际形态划分中,形貌边界较模糊区域可以辅助以物质指标,以保证各类型边界的正确性。

以月海、盆地、月陆、撞击坑4个一级类为基础,根据形态特征,可以分出二级类。月海可分出月海平原和月海穹丘;盆地分为盆底平原和环盆地山丘;月陆分为平原、高原和丘陵;撞击坑可分为主撞击坑、撞击平原、次级撞击坑、撞击坑链、带辐射纹撞击坑、不规则撞击坑、未分撞击坑等(表3)。在第三级类型划分中,可以进一步按照形态和坡面特征、规模进行细化。

3.4 形态—年代相结合分类方案

综合考虑已出版的各类月球形貌类型的划分方案,参考地球地貌类型要反映的形态、成因、物质、年代和过程等几大要素,基于月球形貌类型的划分从形态和物质方面考虑较多,对于年代和大的地质事件的反映不够。为能有效地综合反映月球表面的形貌特征、物质差异和成因状况,提出形态—年代相结合的矩阵式新分类方案(图1,表3)。


图1

基于形态特征和地质年代的月球形貌类型分类体系

Fig.1

Classification system of lunar landform based on morphologic feature and geologic age

图1为基于形态特征和地质年代的全月球形貌类型分类体系,采用2种指标的矩阵组合形式。表3为基于上述2种指标的全月球形貌类型分类矩阵表。由此, 7个年代类,4个一级大类和14个二级形态类型,46种形貌类型被提出(表3)。

表3

基于形态特征和地质年代的月球形貌类型的矩阵式组合分类体系

Table 3

Matrix combination classification system of lunar morphology based on morphologic feature and geologic age

基于以上矩阵式组合分类方案,以H010为案例,制作了月球形貌类型图的各要素图及形貌类型图(图2)。图2a为研究区一级形态特征图,共分为月海、盆地、月陆和撞击坑四大类。图2b为研究区二级形态特征图,包括月海平原、月海穹丘;环盆地山丘;月陆平原、月陆高原和月陆丘陵;主撞击坑、撞击坑链、带辐射纹撞击坑、不规则撞击坑和未分撞击坑。图2c为地质年代图,包括哥白尼纪、哥白尼—爱拉托逊纪过渡、爱拉托逊纪、雨海纪、雨海纪—前雨海纪过渡、前雨海纪。图2d为基于形态特征与地质年代的研究区形貌类型组合。


图2

基于形态类型和地质年代组合而成的H010幅形貌类型制图(a)一级形态;(b)二级形态;(c)年代;(d)形貌组合类型

Fig.2

Maps of morphologic feature, geologic age and landforms of Sheet H010(a)First class morphologic types;(b)Second class morphologic types; (c)Geologic Age; (d) Combined landform types

4 讨 论

(1)地球地貌与月球形貌分类的比较

受地球表面各种外营力及地球自身内营力的共同作用,地球地貌的分类采用多采用形态与成因相结合的分类原则,侧重点在于对内外营力反映程度及表达[79]。通常在大范围小比例尺地貌类型图上,多反映板块构造、大地构造及宏观形态特征;在小范围大比例地貌类型上,多反映地貌形态的差异性、物质组成、坡面特征等。

相比而言,塑造现状月球表面形貌的内外营力方式与地球差异很大[1,2,27~32,78],故月球形貌的分类不能完全借鉴地球地貌的形态与成因相结合的分类方法,受特殊形态及地质年代的控制,提出月球表面的形貌类型采用形态与地质年代相结合的分类方法,以突出月球表面的特殊形貌特征。

(2)月球表面形态特征的多级多指标表达

以往月球形貌分类体系大多只涉及单一类别指标,如形态指标、年代指标、物质指标等,这样一种分类体系往往反映月球表面形貌的单一方面,在分类体系的完备性上略有欠缺。美国月球地质图中的月球形貌分类虽然包含了年代、形态等多种指标,但不同类别指标间的关系并不明确,物质指标与形态指标构成了等级关系,与年代指标则是并列关系,不同类别指标间关系的差异不利于整个分类体系指标的扩充。在本研究提出的分类体系中,以形态指标替代物质指标进行类型划分,采用矩阵式组合方法与年代指标结合,明确统一了不同类别指标间关系,使得整个分类体系的可扩展性大大增强。

从地貌分类的层次性和逻辑性方面来考虑,任何星球的地貌类型都存在等级性,本研究初步提出了月球形态特征的两级类型[27,28,29,30,31,32]。提出该分类思路的意图是在大的形态类型上能全充满月球表面,且大类之间差异明显。月海和月陆的形态差异明显,已有分类中将两者分开。对大型盆地和撞击坑的分类,有研究将两者合在一起,主要认为大型盆地也是撞击作用形成的。本研究中,考虑到大型盆地不全是撞击坑作用的结果,将大型盆地和撞击坑分为两大类,以突出大型盆地和撞击坑的规模和成因差异。在此基础上,将四大类形态特征依据各自的指标体系逐级进行细化。

(3)撞击坑形貌分类与表达

目前对撞击坑形貌类型的分类方案研究相对较多,王娇等[26]照形态和规模相结合的比对指标,将全月球撞击坑分为月海残留型、特大复杂型、大环状平原型、中等凹坑平原型、小规模碗型和微状酒窝型六大类,这种分类方案适合于只研究撞击坑类型。考虑到全月球的形貌类型划分,本方案对各种撞击坑分类进行了综合,分为主撞击坑、撞击平原、次级撞击坑、撞击坑链、带辐射纹撞击坑、不规则撞击坑和未分撞击坑等七大类,将撞击坑链、带辐射纹的撞击坑单独分出来,以突出它们的形态差异性、撞击作用和时间特征[27,28,29,30,31,32]

(4)基础地理信息和形貌类型的表达

地貌类型图既要表示各级形貌类型,也要在其上叠加基础地理的诸多信息,如地名、山脉等[82,83,84,85]。跟地球地貌图相似的是,到目前为止,月球上已命名了多种大小不同的基础地理地名,包括月洋(风暴洋)、月海(包括蛇海、南海、知海、危海、丰富海、冷海、洪堡海、湿海、雨海、智海、岛海、界海、莫斯科海、酒海、云海、东海、澄海、史密斯海、泡海、静海、浪海和汽海,共22个)、月湖(包括夏湖等,共20个)、平原(降落平原)、山脉(包括高加索山脉等,共48个)、山脊(包括阿尔甘山脊等,共39个)、环形坑和卫星坑(已命名的有近9 000个)、峭壁(包括阿尔泰峭壁等,共8个)、坑链(包括洪堡坑链等,共19个)、月谷(包括阿尔卑斯月谷等,共14个)、海角(包括开尔文海角等,共9个)、月溪(包括杨森月溪等,共115个)、月湾(包括虹湾等,共11处)、月沼(包括梦沼等,共3处)、反照率特征点(包括赖纳伽马)、月球着陆点(包括博特朗等,共79处)[84,85]。上述基础地理的部分信息也是较细一级的形貌类型。因此,在较详细的形貌类型分类中,按照相对应的指标体系将其划分出具有一定面积的图斑,在基础地理信息中,也反映出相应的名称。

5 结 论

考虑到月球表面形貌的现状特征、受宏观营力格局及作用方式、形态变异及组合特征等,初步提出了基于形态和年代两大类特征相结合全月球形貌类型的矩阵式多级分类方法。

全月球形貌类型中,按照宏观形态及营力作用方式,可将第一级划分为月海、盆地、月陆和撞击坑四大类。第二级中,按照大类的形态差异性,将盆地分为盆底平原和环盆地山丘;月海分为月海平原和月海穹丘;月陆分为月陆平原、月陆丘陵和月陆高原;撞击坑按照形态和规模分为特大型撞击坑环形山、特大型撞击平原、次级形成小撞击坑、撞击坑链、带辐射纹撞击坑、不规则和边缘模糊坑、未分形态撞击坑等类型。根据坡面和物质差异,可细化出三级甚至四级形态类型。而年代可分为哥白尼纪、爱拉托逊纪、雨海纪、前雨海纪、及两者之间的过渡年代等七大类。

以H010幅为案例,对形态类型、地质年代2种指标和组合形貌类型进行了制图试验。本研究将对全月球形貌类型的划分和制图具有一定的指导作用。

The authors have declared that no competing interests exist.

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<p>利用&ldquo;嫦娥一号&rdquo;CCD 相机获得的遥感影像及其经三线阵数字摄影测量处理后的DEM数据(空间分辨率为500 m)进行了月表形貌特征分析. 结果表明: 月球的平均高程为&ndash;742 m,最大高程点和最小高程点均位于月球的背面, 其中前者位于Engel&rsquo;gardt 撞击坑东缘, 后者位于Minkowski 撞击坑的次级撞击坑内; 月球表面相对平坦, 大部分坡度在15&deg;以下, 占月球总面积的90%, 月球高地的坡度值变化较大, 平均坡度大于7&deg;, 月海坡度变化较小, 多数在3&deg;以下; 月表起伏度计算的最佳统计窗口为16 km<sup>2</sup>, 大部分区域起伏度在200 m 以下, 而起伏度大于2000 m 的大起伏山地主要分布在撞击坑周围的环形山区域; 基于高程、坡度、起伏度及影像灰度值的归一化处理数据, 利用最大似然法进行月海和月球高地的自动提取, 其结果与美国地质调查局出版的地质图进行精度评价, 获得Kappa 系数为0.78, 该方法可以较好地进行月球形态特征的提取及分析.</p>
[周增坡, 程维明, 周成虎, . 基于“嫦娥一号”的月球表面形貌特征分析与自动提取[J]. 科学通报, 2011, 56(1): 18-26.]
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<p>利用&ldquo;嫦娥一号&rdquo;CCD 相机获得的遥感影像及其经三线阵数字摄影测量处理后的DEM数据(空间分辨率为500 m)进行了月表形貌特征分析. 结果表明: 月球的平均高程为&ndash;742 m,最大高程点和最小高程点均位于月球的背面, 其中前者位于Engel&rsquo;gardt 撞击坑东缘, 后者位于Minkowski 撞击坑的次级撞击坑内; 月球表面相对平坦, 大部分坡度在15&deg;以下, 占月球总面积的90%, 月球高地的坡度值变化较大, 平均坡度大于7&deg;, 月海坡度变化较小, 多数在3&deg;以下; 月表起伏度计算的最佳统计窗口为16 km<sup>2</sup>, 大部分区域起伏度在200 m 以下, 而起伏度大于2000 m 的大起伏山地主要分布在撞击坑周围的环形山区域; 基于高程、坡度、起伏度及影像灰度值的归一化处理数据, 利用最大似然法进行月海和月球高地的自动提取, 其结果与美国地质调查局出版的地质图进行精度评价, 获得Kappa 系数为0.78, 该方法可以较好地进行月球形态特征的提取及分析.</p>
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[丁孝忠, 韩坤英, 韩同林, . 月球虹湾幅(LQ-4)地质图的编制[J]. 地学前缘, 2012, 19(6): 15-27.]
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应用中国首次月球探测工程所获得的嫦娥一号(Change-I)CCD影像数据、干涉成像光谱数据、数字高程模型(DEM)数据和数据分析处理结果等资料,开展了虹湾—雨海地区区域地质综合研究。通过对月球撞击坑及溅射堆积物分析,以及地层单元划分、构造单元划分、岩石类型划分、年代学和月球演化历史的集成分析,依据月坑的形态特征、充填物的多少和保留的程度等,将月球撞击坑划分出7种类型11个亚类,并将月球撞击坑堆积物系统划分为6种类型9个堆积岩组。根据TiO2的含量、分布及影像特征,将月海、月陆玄武岩划分为高钛玄武岩、中钛玄武岩和低钛玄武岩。应用ArcGIS地理信息系统,试点编制了1∶250万月球典型地区——虹湾幅(LQ-4)地质图,并建立了空间数据库,探索制定了月球数字地质图编制技术规范、流程和方法,为中国下一步应用嫦娥二号数据开展"全月球地质图"编制,以及未来其他天体的区域地质综合研究与地质编图工作奠定了基础。
[本文引用: 1]
[34]
Chen Jianping, Wang Xiang, Xu Yanbo, et al. Compilation of the lunar geotectonic outline map based on multisource data:A case study of LQ-4 Area[J]. Earth Science Frontiers, 2012, 19(6): 1-14 .
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月球表面的地质构造要素主要包括环形构造、线性构造、地体构造及大型盆地构造等。月球大地构造纲要图从物质组成、构造要素、构造单元上对月表的构造状态进行全面的梳理、统计和分析。利用CE-1CCD 2C像数据、LROC宽视角影像数据、CE-1IIM 2C干涉成像光谱仪数据、Clementine紫外可见光影像数据、LOLA激光高度计数据识别月球表面各类矿物组分、线形构造、环形构造、火山构造和穹窿构造以及确定构造要素和构造单元的时代、古老撞击坑和大型盆地边界以及对月球表面撞击坑形态、大小、分布、密度及月球断裂和环形影像解译,充分认识月表基本情况,精细划分月表构造地貌单元,综合利用上述分析结果与国际上研究的进展,确定大地构造区划的基本原则,厘定月表重大构造事件与演化序列。依据岩石、月壤、构造地貌与构造形迹的综合分类,拟定大地构造区划的图例、图识规范,确定不同类型环形构造影像、线性构造影像、高地、盆地和月海等大地构造单元,进而编制大地构造区划图,并对重点区域构造形迹进行研究。虹湾区域(LQ-4)月球数字构造编图研究,充分借鉴国际行星地质编图的已有技术标准和规范,结合国内数字地质编图的技术标准和规范,建立了中国自己的月球与行星地质编图标准、规范和制图流程,也为最终完成月球大地构造区划提供地貌和构造方面的基础信息。
[陈建平, 王翔, 许延波, . 基于多源数据的月球大地构造纲要图编制:以LQ-4地区为例[J]. 地学前缘, 2012, 19(6): 1-14.]
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月球表面的地质构造要素主要包括环形构造、线性构造、地体构造及大型盆地构造等。月球大地构造纲要图从物质组成、构造要素、构造单元上对月表的构造状态进行全面的梳理、统计和分析。利用CE-1CCD 2C像数据、LROC宽视角影像数据、CE-1IIM 2C干涉成像光谱仪数据、Clementine紫外可见光影像数据、LOLA激光高度计数据识别月球表面各类矿物组分、线形构造、环形构造、火山构造和穹窿构造以及确定构造要素和构造单元的时代、古老撞击坑和大型盆地边界以及对月球表面撞击坑形态、大小、分布、密度及月球断裂和环形影像解译,充分认识月表基本情况,精细划分月表构造地貌单元,综合利用上述分析结果与国际上研究的进展,确定大地构造区划的基本原则,厘定月表重大构造事件与演化序列。依据岩石、月壤、构造地貌与构造形迹的综合分类,拟定大地构造区划的图例、图识规范,确定不同类型环形构造影像、线性构造影像、高地、盆地和月海等大地构造单元,进而编制大地构造区划图,并对重点区域构造形迹进行研究。虹湾区域(LQ-4)月球数字构造编图研究,充分借鉴国际行星地质编图的已有技术标准和规范,结合国内数字地质编图的技术标准和规范,建立了中国自己的月球与行星地质编图标准、规范和制图流程,也为最终完成月球大地构造区划提供地貌和构造方面的基础信息。
[本文引用: 1]
[35]
Ouyang Ziyuan, Liu Jianzhong.The origin and evolution of the Moon and its geological mapping[J]. Earth Science Frontiers, 2014, 21(6): 1-6 .
DOI:10.13745/j.esf.2014.06.001 URL
按照大碰撞假说,月球形成于一次大碰撞事件,抛射出的高能量物质留在绕地轨道上,最后吸积形成月球。月球核幔在早期迅速发生分离,并出现全球性的岩浆熔融,形成了岩浆圈层(岩浆洋)。岩浆洋的结晶分异和固化导致了月壳的形成。随着月壳与月幔发生持续分异,形成了固化的月壳。而在月球后期的演化历史中,撞击作用是最重要的地质作用,形成了多尺度、多期次的撞击盆地和撞击坑,而大型撞击盆地多形成于月球演化的早期。月球地质图是开展月球形成与演化研究的重要手段,从20世纪60年代起,到70年代末止,通过对阿波罗时代探月成果的系统总结,完成了第一轮月球地质图的研制。但尽管从20世纪90年代以来国际月球探测和月球科学的研究进入一个新的高潮,获得了大量有关月球形成和演化的新认识,但还没有正式的新的月球地质图发布,因此开展新一轮月球地质图的编研,系统总结后阿波罗时代的月球探测与研究成果,是非常必要和迫切的。在新一轮月球地质图的编制过程中,需重点关注图件比例尺的选择、月面历史的划分以及月球构造和岩石建造的表达。
[欧阳自远, 刘建忠. 月球形成演化与月球地质图编研[J]. 地学前缘, 2014, 21(6): 1-6.]
DOI:10.13745/j.esf.2014.06.001 URL
按照大碰撞假说,月球形成于一次大碰撞事件,抛射出的高能量物质留在绕地轨道上,最后吸积形成月球。月球核幔在早期迅速发生分离,并出现全球性的岩浆熔融,形成了岩浆圈层(岩浆洋)。岩浆洋的结晶分异和固化导致了月壳的形成。随着月壳与月幔发生持续分异,形成了固化的月壳。而在月球后期的演化历史中,撞击作用是最重要的地质作用,形成了多尺度、多期次的撞击盆地和撞击坑,而大型撞击盆地多形成于月球演化的早期。月球地质图是开展月球形成与演化研究的重要手段,从20世纪60年代起,到70年代末止,通过对阿波罗时代探月成果的系统总结,完成了第一轮月球地质图的研制。但尽管从20世纪90年代以来国际月球探测和月球科学的研究进入一个新的高潮,获得了大量有关月球形成和演化的新认识,但还没有正式的新的月球地质图发布,因此开展新一轮月球地质图的编研,系统总结后阿波罗时代的月球探测与研究成果,是非常必要和迫切的。在新一轮月球地质图的编制过程中,需重点关注图件比例尺的选择、月面历史的划分以及月球构造和岩石建造的表达。
[本文引用: 2]
[36]
Chen Jianping, Wang Xiang, Wang Nan, et al. The lunar geological mapping based on Chang'E data: Serenitatis-Tranquillitatis area as an example[J]. Earth Science Frontiers, 2014, 21(6): 7-18 .
[陈建平, 王翔, 王楠, . 基于嫦娥数据澄海—静海幅地质图编研[J]. 地学前缘, 2014, 21(6): 7-18.]
[本文引用: 1]
[37]
Florinsky I V.Global Morphometric Maps of Mars, Venus, and the Moon[M]. Berlin, Germany: Springer, 2008.
[本文引用: 1]
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Rosenburg M A, Aharonson O, Head J W, et al. Global surface slopes and roughness of the Moon from the Lunar Orbiter Laser Altimeter[J].Journal of Geophysical Research: Planets, 2011, 116(E2): 1-11.
[本文引用: 1]
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Xi Xiaoxu, Liu Shaofeng, Wu Zhiyuan, et al. The interpretation of land form of Sinus Iridum on the Moon based on the roughness[J].Remote Sensing for Land and Resources, 2012, 92(1): 95-99 .
DOI:10.6046/gtzyyg.2012.01.17 URL
The planetary surface roughness is the record of erosion, deposition, uplift and other geological processes on the planetary surface, and hence serves as a prediction for the geological age of the planetary surface. In this paper, twelve profiles were selected in the horizontal direction of the Sinus Iridum in the moon, and several parameters of roughness of those profiles were studied. Some results have been obtained: 1The average of RMS height along the profile 1 km in length is about 3m. In addition, within the research scale selected in this paper (0.2~3 km), the slope of Sinus Iridum area does not exceed 2?. This means that the surface of Sinus Iridum is relatively smooth. 2Hurst exponent of Sinus Iridum is mainly concentrated from 0.5 to 0.78, which means that the surface morphology is rather homogeneous. 3Low latitude areas(lower than 44.3)have relatively high Hurst exponent (from 0.6 to 0.8), and high latitude areas(higher than 44.3)usually have lower Hurst exponent (from 0.5 to 0.8). 4The roughness may be used as a means to determine the relative geological age.
[奚晓旭,刘少峰,吴志远,. 基于粗糙度的月球表面虹湾地区地形地貌解译[J]. 国土资源遥感, 2012, 92(1): 95-99.]
DOI:10.6046/gtzyyg.2012.01.17 URL
The planetary surface roughness is the record of erosion, deposition, uplift and other geological processes on the planetary surface, and hence serves as a prediction for the geological age of the planetary surface. In this paper, twelve profiles were selected in the horizontal direction of the Sinus Iridum in the moon, and several parameters of roughness of those profiles were studied. Some results have been obtained: 1The average of RMS height along the profile 1 km in length is about 3m. In addition, within the research scale selected in this paper (0.2~3 km), the slope of Sinus Iridum area does not exceed 2?. This means that the surface of Sinus Iridum is relatively smooth. 2Hurst exponent of Sinus Iridum is mainly concentrated from 0.5 to 0.78, which means that the surface morphology is rather homogeneous. 3Low latitude areas(lower than 44.3)have relatively high Hurst exponent (from 0.6 to 0.8), and high latitude areas(higher than 44.3)usually have lower Hurst exponent (from 0.5 to 0.8). 4The roughness may be used as a means to determine the relative geological age.
[本文引用: 1]
[40]
Wang Chenzhi, Tang Guoan, Yuan Sai, et al. A method for identifying the lunar morphology based on texture from DEMs[J].Journal of Geo-information Science, 2015, 17(1): 45-53 .
DOI:10.3724/SP.J.1047.2015.00045 Magsci URL
<p>月海和月陆是两种最主要的月貌单元,对于月海及月陆快速准确地识别是进行各项月球研究的重要基础。目前,月海和月陆的识别大多采用DEM结合其派生地形因子建立指标体系的方法。这种方法虽然可在宏观尺度对月海和月陆进行识别和提取,但仍存在2 个问题:(1)可扩展性差,不同地区难以共用同一套地形因子构建指标体系;(2)指标体系中各因子权重设置具有较大的主观性。针对以上问题,本文以&ldquo;嫦娥一号&rdquo;探测器获取的全月球DEM数据,从月表地形纹理特征的角度出发,提出一种以月表DEM数据识别月海、月陆的自动快速的方法。首先,利用灰度共生矩阵模型,以DEM数据为基础,实现对典型月海、月陆地形纹理特征的量化,然后,对量化指标的筛选,构建能有效区分两类月表形貌单元的特征向量。在此基础上,选用离差平方和作为识别器,最终实现对月海和月陆的自动识别。本文识别方法的整体识别率达到85.7%;综上可知,该方法既能克服原有方法中因子权重设置的主观性,又具有较好的通用性。</p>
[王琛智,汤国安,袁赛,. 基于DEM 纹理特征的月貌自动识别方法探究[J]. 地球信息科学学报, 2015, 17(1): 45-53.]
DOI:10.3724/SP.J.1047.2015.00045 Magsci URL
<p>月海和月陆是两种最主要的月貌单元,对于月海及月陆快速准确地识别是进行各项月球研究的重要基础。目前,月海和月陆的识别大多采用DEM结合其派生地形因子建立指标体系的方法。这种方法虽然可在宏观尺度对月海和月陆进行识别和提取,但仍存在2 个问题:(1)可扩展性差,不同地区难以共用同一套地形因子构建指标体系;(2)指标体系中各因子权重设置具有较大的主观性。针对以上问题,本文以&ldquo;嫦娥一号&rdquo;探测器获取的全月球DEM数据,从月表地形纹理特征的角度出发,提出一种以月表DEM数据识别月海、月陆的自动快速的方法。首先,利用灰度共生矩阵模型,以DEM数据为基础,实现对典型月海、月陆地形纹理特征的量化,然后,对量化指标的筛选,构建能有效区分两类月表形貌单元的特征向量。在此基础上,选用离差平方和作为识别器,最终实现对月海和月陆的自动识别。本文识别方法的整体识别率达到85.7%;综上可知,该方法既能克服原有方法中因子权重设置的主观性,又具有较好的通用性。</p>
[本文引用: 1]
[41]
Bue B D, Stepinski T F.Automated classification of landforms on Mars[J].Computers and Geosciences, 2006, 32(5): 604-614.
DOI:10.1016/j.cageo.2005.09.004 URL
We propose a numerical method for classification and characterization of landforms on Mars. The method provides an alternative to manual geomorphic mapping of the Martian surface. Digital elevation data is used to calculate several topographic attributes for each pixel in a landscape. Unsupervised classification, based on the self-organizing map technique, divides all pixels into mutually exclusive and exhaustive landform classes on the basis of similarity between attribute vectors. The results are displayed as a thematic map of landforms and statistics of attributes are used to assign semantic meaning to the classes. This method is used to produce a geomorphic map of the Terra Cimmeria region on Mars. We assess the quality of the automated classification and discuss differences between results of automated and manual mappings. Potential applications of our method, including crater counting, landscape feature search, and large scale quantitative comparisons of Martian surface morphology, are identified and evaluated.
[本文引用: 2]
[42]
Li Jing, Chen Jianping, Wang Nan, et al. A new automated approach to detecting and extracting the linear structures on the lunar surface: A case study on the lunar mare ridge of Mare Serenitatis[J]. Earth Science Frontiers, 2014, 21(6): 223-228 .
[李婧, 陈建平, 王楠, . 月球表面线性构造自动提取新方法研究: 以澄海地区月岭为例[J]. 地学前缘, 2014, 21(6): 223-228.]
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[43]
Li Ke, Chen Jianping, Tarolli P, et al. Geomorphometric multi-scale analysis for the automatic detection of linear structures on the lunar surface[J]. Earth Science Frontiers, 2014, 21(6):212-222 .
DOI:10.13745/j.esf.2014.06.021 URL
月球表面构造对于理解和重建月球地质构造演化具有重要意义,月岭、月溪等线性构造的形态及分布特征与月球内动力构造运动密切相关。极为有限的样品和难度极高的野外勘察使得遥感成为行星科学研究的最主要手段。中国、美国、日本、印度等国先后发射的多颗新型探月卫星获取了大量高质量数据,尤其是高分辨率的数字地形数据(DTM,Digital Terrain Model)。高分辨率的DTM为月球表面构造特征的自动提取带来了新的机遇与挑战。文中利用多种分辨率的DTM数据,基于多尺度数字地形定量分析方法,识别和提取月球表面的线性构造。使用的地形数据包括500m分辨率"嫦娥一号"激光高度计数据,100m分辨率LRO-WAC广角相机数据,60m分辨率的LRO-LOLA激光测距仪数据以及分辨率高达5m的LRO-NAC窄视角相机数据。文中使用地形曲率来识别月溪月岭等线性构造,并利用不同滑动窗口大小和阈值进行线性构造的自动提取。对研究区试验结果的定量分析表明,文中提出的基于地形曲率的月表线性构造自动提取方法是有效且可行的,其结果可为月球表面线性构造解译提供重要参考,提高构造解译时效性和精度。
[李珂,陈建平,Tarolli Paolo,. 基于多尺度数字地形定量分析的月球线性构造自动提取研究[J]. 地学前缘, 2014, 21(6): 212-222.]
DOI:10.13745/j.esf.2014.06.021 URL
月球表面构造对于理解和重建月球地质构造演化具有重要意义,月岭、月溪等线性构造的形态及分布特征与月球内动力构造运动密切相关。极为有限的样品和难度极高的野外勘察使得遥感成为行星科学研究的最主要手段。中国、美国、日本、印度等国先后发射的多颗新型探月卫星获取了大量高质量数据,尤其是高分辨率的数字地形数据(DTM,Digital Terrain Model)。高分辨率的DTM为月球表面构造特征的自动提取带来了新的机遇与挑战。文中利用多种分辨率的DTM数据,基于多尺度数字地形定量分析方法,识别和提取月球表面的线性构造。使用的地形数据包括500m分辨率"嫦娥一号"激光高度计数据,100m分辨率LRO-WAC广角相机数据,60m分辨率的LRO-LOLA激光测距仪数据以及分辨率高达5m的LRO-NAC窄视角相机数据。文中使用地形曲率来识别月溪月岭等线性构造,并利用不同滑动窗口大小和阈值进行线性构造的自动提取。对研究区试验结果的定量分析表明,文中提出的基于地形曲率的月表线性构造自动提取方法是有效且可行的,其结果可为月球表面线性构造解译提供重要参考,提高构造解译时效性和精度。
[本文引用: 2]
[44]
Wang Nan.Automated Extraction and Evolution Analysis of the Lineaments on Mare Tranquillitatis of the Moon[D]. Beijing: China University of Geosciences, 2015 .
[王楠. 月球静海地区线性构造自动提取与演化分析[D]. 北京: 中国地质大学, 2015.]
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Chabot N L, Hoppa G V, Strom R G.Analysis of lunar lineaments: Far side and polar mapping[J].Icarus, 2000, 147(1): 301-308.
DOI:10.1006/icar.2000.6433 URL
Previous mapping of linear structures on the lunar near side shows that lineaments are not equally oriented in all directions but rather have preferred orientations. The preferred orientations of near-side lunar lineaments are roughly consistent with the tectonic pattern predicted by relaxation of a formerly larger tidal bulge on the Moon due to the Moon's continuing recession from the Earth. We have mapped lineaments on the lunar far side and both the polar regions as well as re-examined lineaments mapped in the sub-Earth and anti-Earth regions to determine if the lineament patterns observed in these regions are also consistent with being produced by the collapse of a once larger tidal bulge on the Moon. The lunar far side is found to have a lineament pattern similar to that previously observed on the near side, which is consistent with being produced by the collapse of a once larger tidal bulge. However, the sub-Earth and anti-Earth regions show a lineament pattern indistinguishable from that observed on the rest of the lunar near and far sides, even though relaxation of a formerly larger tidal bulge would produce a significantly different pattern in these regions. Collapse of a once larger tidal bulge also predicts a near to far side lineament trend in the lunar polar regions, but mapped lineaments in the polar regions show no evidence for such a trend. Overall, the observed lunar lineament patterns do not support the predictions of a global tectonic pattern due to the collapse of a once larger tidal bulge on the Moon and therefore require an alternate explanation.
[本文引用: 2]
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Neukum G, König B, Arkani-Hamed J.A study of lunar impact crater size-distributions[J]. Moon, 1975, 12(2):201-229.
DOI:10.1007/BF00577878 URL
Discrepancies in published crater frequency data prompted this study of lunar crater distributions. Effects modifying production size distributions of impact craters such as surface lava flows, blanketing by ejecta, superposition, infilling, and abrasion of craters, mass wasting, and the contribution of secondary and volcanic craters are discussed. The resulting criteria have been applied in the determination of the size distributions of unmodified impact crater populations in selected lunar regions of different ages. The measured cumulative crater frequencies are used to obtain a general calibration size distribution curve by a normalization procedure. It is found that the lunar impact crater size distribution is largely constant in the size range 0.3 km 81 D 81 20 km for regions with formation ages between ≈ 3 × 10 9 yr and 68 4 × 10 9 yr. A polynomial of 4th degree, valid in the size range 0.8 km 81 D 81 20 km, and a polynomial of 7th degree, valid in the size range 0.3 km 81 D 81 81 20 km, have been approximated to the logarithm of the cumulative crater frequency N as a function of the logarithm of crater diameter D. The resulting relationship can be expressed as N 65 D α ( D ) where α is a function depending on D. This relationship allows the comparison of crater frequencies in different size ranges. Exponential relationships with constant α, commonly used in the literature, are shown to inadequately approximate the lunar impact crater size distribution. Deviations of measured size distributions from the calibration distribution are strongly suggestive of the existence of processes having modified the primary impact crater population.
[本文引用: 2]
[47]
Yue Zongyu, Liu Jianzhong, Wu Ganguo.Automated detection of lunar craters based on object-oriented approach[J]. Chinese Science Bulletin, 2008, 53(23): 3 699-3 704.
DOI:10.1007/s11434-008-0413-3 URL
The object-oriented approach is a powerful method in making classification. With the segmentation of images to objects, many features can be calculated based on the objects so that the targets can be distinguished. However, this method has not been applied to lunar study. In this paper we attempt to apply this method to detecting lunar craters with promising results. Craters are the most obvious features on the moon and they are important for lunar geologic study. One of the important questions in lunar research is to estimate lunar surface ages by examination of crater density per unit area. Hence, proper detection of lunar craters is necessary. Manual crater identification is inefficient, and a more efficient and effective method is needed. This paper describes an object-oriented method to detect lunar craters using lunar reflectance images. In the method, many objects were first segmented from the image based on size, shape, color, and the weights to every layer. Then the feature of “contrast to neighbor objects” was selected to identify craters from the lunar image. In the next step, by merging the adjacent objects belonging to the same class, almost every crater can be taken as an independent object except several very big craters in the study area. To remove the crater rays diagnosed as craters, the feature of “length/width” was further used with suitable parameters to finish recognizing craters. Finally, the result was exported to ArcGIS for manual modification to those big craters and the number of craters was acquired.
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Moutsoulas M, Preka P.Morphological characteristics of lunar craters with small depth/diameter ratio I[J].Earth, Moon and Planets, 1979, 21(3): 299-305.
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Ding Meng, Cao Yunfeng, Wu Qingxian.A method of craters detection from the surface imagery of Moon[J]. Journal of Astronautics, 2009, 30(3): 1 243-1 248.
DOI:10.1016/0021-9614(78)90029-0 URL
As the development of China's Lunar Exploration,Vision-Based technology of lunar probe autonomous landing is researching.Craters are commonly found on the surface of moon.The crater detection from surface images,as a key technology of Autonomous Hazard Avoidance,has been researched by many scientists from different countries.In this paper,a new algorithm based on feature point is demonstrated.The algorithm is divided into three parts,feature points extraction,candidate area of crater decision and crater detection.Firstly,candidate areas of crater are decided by feature point extraction.Secondly,the light and shaded parts of crater are extracted by region growing.Finally,the craters are detected by ellipse detection.Experiment result shows this algorithm is effective for some craters detection.Those craters have strong intensity variations and their radiuses are longer than 5 pixels and shorter than 15 pixels.In the conclusion,authors offer four improvement directions of this algorithm in the future.
[本文引用: 2]
[51]
Du Jun, Miao Fang, Lu Yuhang, et al. Research on appraisal of edge definition of impact craters[J]. Computer Engineering and Applications, 2013,49(15): 179-183 .
Magsci URL
撞击坑是月球表面最重要的地质构造之一,通过对&ldquo;嫦娥一号&rdquo;CCD影像中撞击坑的边缘清晰度进行评价,可以进一步反演出月球表面的风化程度、地表起伏等地质信息。提出一种基于图像清晰度评价的边缘清晰度评价方法,从空域的梯度、频域的高频分量以及信息论三个方面,运用基于Sobel算子、小波变换和信息熵的算法对撞击坑的边缘清晰度予以评价。设计出一种适应于月球撞击坑特征的BP神经网络,组合三种评价算法的结果作为其输入,进而得到最终的清晰度等级。将最终结果加载到具有自主知识产权的数字月球平台上予以全月性的展示和进一步分析。
[都骏, 苗放, 鲁宇航, . 月球撞击坑边缘清晰度评价方法的研究[J]. 计算机工程与应用, 2013,49(15): 179-183.]
Magsci URL
撞击坑是月球表面最重要的地质构造之一,通过对&ldquo;嫦娥一号&rdquo;CCD影像中撞击坑的边缘清晰度进行评价,可以进一步反演出月球表面的风化程度、地表起伏等地质信息。提出一种基于图像清晰度评价的边缘清晰度评价方法,从空域的梯度、频域的高频分量以及信息论三个方面,运用基于Sobel算子、小波变换和信息熵的算法对撞击坑的边缘清晰度予以评价。设计出一种适应于月球撞击坑特征的BP神经网络,组合三种评价算法的结果作为其输入,进而得到最终的清晰度等级。将最终结果加载到具有自主知识产权的数字月球平台上予以全月性的展示和进一步分析。
[本文引用: 1]
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Bijaoui A, Froeschle M M.A new algorithm to determine image edges—Application to lunar craters[J]. Astronomy and Astrophysics, 1980, 87(1/2): 250-251.
URL
A new algorithm based on an analytical expression of the density has been developed for edge determination in lunar studies. Use was made of a digital microdensitometer and a two-dimensional sliding mean filter. Attention is given to the use of the Laplacian and to maximum gradient lines. The proposed algorithm has been tested with about sixty craters, and good crater measurements have been obtained.
[本文引用: 1]
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Canny J.A computational approach to edge detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, 8(6): 679-698.
URL
Abstract-This paper describes a computational approach to edge detection. The success of the approach depends on the definition of a comprehensive set of goals for the computation of edge points. These goals must be precise enough to delimit the desired behavior of the detector while making minimal assumptions about the form of the so- lution. We define detection and localization criteria for a class of edges, and present mathematical forms for these criteria as functionals on the operator impulse response. A third criterion is then added to ensure that the detector has only one response to- a single edge. We use the criteria in numerical optimization to derive detectors for several com- mon image features, including step edges. On specializing the analysis to step edges, we find that there is a natural uncertainty principle be- tween detection and localization performance, which are the two main goals. With this principle we derive a single operator shape which is optimal at any scale. The optimal detector has a simple approximate implementation in which edges are marked at maxima in gradient mag- nitude of a Gaussian-smoothed image. We extend this simple detector using operators of several widths to cope with different signal-to-noise ratios in the image. We present a general method, called feature syn- thesis, for the fine-to-coarse integration of information from operators at different scales. Finally we show that step edge detector perfor- mance improves considerably as the operator point spread function is extended along the edge. This detection scheme uses several elongated operators at each point, and the directional operator outputs are in- tegrated with the gradient maximum detector.
[本文引用: 1]
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Salamunićcar G, Lončarić S, Mazarico E. LU60645GT and MA132843GT catalogues of Lunar and Martian impact craters developed using a Crater Shape—Based interpolation crater detection algorithm for topography data[J]. Planetary and Space Science, 2012, 60(1): 236-247.
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Yuan Yuefeng, Zhu Peimin, Zhao Na, et al. Automatic identification of circular mare craters based on mathematical morphology[J]. Scientia Sinica Physica, Mechanica and Astronomica, 2013,43(3): 324-332 .
[袁悦锋, 朱培民, 赵娜, . 基于数学形态学的月海圆形撞击坑自动识别方法[J]. 中国科学: 物理学, 力学, 天文学,2013, 43(3): 324-332.]
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Michael G G.Coordinate registration by automated crater recognition[J]. Planetary and Space Science, 2003, 51(9): 563-568.
DOI:10.1016/S0032-0633(03)00074-6 URL
An algorithm for the automatic recognition of impact craters is presented, based on Hough transforms and accounting for both the circularity of the crater rim and the presence of the internal depression. The algorithm is applied to adjust a catalogue of crater coordinates originally measured in the context of the USGS 1:2M controlled photomosaic to the more precise geodetic grid derived from the Mars Orbiter Laser Altimeter experiment of the Mars Global Surveyor mission. The transformed coordinates are used to generate a global displacement field which may be used as a general transformation between the two coordinate systems. The feasibility of using the new coordinates to extract topographic profiles passing through the crater centres is demonstrated. The potential application of the algorithm for surface dating using the HRSC stereoscopic images and for searching for unknown impact structures on the Earth is discussed.
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Kim J R, Muller J P, Mor ley J G. Quantitative assessment of automated crater detection on Mars[C]//2004 ISPRS Congress. Istanbul, Turkey: ISPRS, 2004.
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Leroy B, Medioni G, Johnson E, et al. Crater detection for autonomous landing on asteroids[J]. Image and Vision Computing, 2001, 19(11): 787-792.
DOI:10.1016/S0262-8856(00)00111-6 URL
We describe a visual positioning system for use by a spacecraft to choose a landing site, while orbiting an asteroid. The spacecraft pose is refined using landmarks, such as craters, observed by a visual sensor. The craters, which have an elliptical shape, are detected using a multi-scale method based on voting, and tensors as a representation. We propose a new robust method to infer curvature estimation from noisy sparse data. This method is applied on edge images in order to obtain the oriented normals of the edge curves. Using this information, a dense saliency map corresponding to the position and shape of the craters is computed. The detected craters in the image are matched with the craters projected from a 3D model, and the best transformation between these two sets is obtained. This system has been tested with both real images of Phobos and a synthetic model.
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He Jiang.Research on Crater Matching Based Navigation Method for Lunar Precise Landing[D]. Haerbing: Harbin Institute of Technology, 2010 .
[何江. 基于陨石坑匹配的月球精确着陆导航方法研究[D]. 哈尔滨: 哈尔滨工业大学, 2010.]
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Plesko C S, Werner S C, Brumby S P, et al. A statistical analysis of automated crater counts in MOC and HRSC data[C]//37th Annual Lunar and Planetary Science Conference. League City,Texas: Lunar and Planetary Institute, 2006.
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Honda R, Iijima Y, Konishi O.Mining of topographic feature from heterogeneous imagery and its application to lunar craters[C]//Proceeding of the Progress of Discovery Science. Berlin, Germany: Springer, 2002.
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Sawabe Y, Matsunaga T, Rokugawa S.Automated detection and classification of lunar craters using multiple approaches[J].Advances in Space Research, 2006, 37(1): 21-27.
DOI:10.1016/j.asr.2005.08.022 URL
Our previous algorithm (Sawabe, Y., Matsunaga, T., Rokugawa, S. Automatic crater detection algorithm for the lunar surface using multiple approaches. J. Remote Sens. Soc. Jpn. 25 (2), 157–168, 2005.) was improved to enhance detection of craters in lunar images and automate crater classification. This algorithm was tested using various images for wide range of applicability. Four approaches were used with the crater detecting algorithm to find (1) “shady and sunny” patters in images with low sun angle, (2) circular features in edge images, (3) curves and circles in thinned and connected edge lines, and (4) discrete or broken circular edge lines using fuzzy Hough transform. The algorithm was applied to mare and highland images of the moon captured by Clementine and Apollo under different solar angles and spatial resolution. The new algorithm was able to detect 80% more without parameter tuning. In addition, the detected craters were classified by spectral characteristics derived from Clementine UV–Vis multi-spectral images. Finally, the lunar surface GIS was formulated which has the geological and spectral attributes automatically generated by our algorithm. It could be helpful system to analyze and recognize about the geological settings.
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Burl M C, Stough T, Colwell W, et al. Automated detection of craters and other geological features[C]//6th International Symposium on Artificial Intelligence, Robotics and Automation in Space. United States: NASA Technical Reports Server, 2001.
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Wan Cong, Cheng Weiming, Zhou Zengpo, et al. Automatic extraction of lunar impact craters from Chang'E-1 satellite photographs[J]. Science China, Physics, Mechanics and Astronomy, 2012, 55(1): 162-169.
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Salamunićcar G, Lončarić S. Method for crater detection from Martian digital topography data using gradient value orientation, morphometry, votes-analysis, slip-tuning and calibration[J]. IEEE Transaction on Geoscience and Remote Sensing, 2010, 48(5): 2 317-2 329.
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Salamunićcar G, Lončarić S, Vinković D, et al. Test-field for evaluation of laboratory craters using a Crater Shape—Based interpolation crater detection algorithm and comparison with Martian and Lunar impact craters[J]. Planetary and Space Science, 2012, 71(1): 106-118.
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Luo Lei, Mu Lingli, Wang Xinyuan, et al. Global detection of large lunar craters based on the CE-1 digital elevation model[J].Frontiers of Earth Science, 2013, 7(4): 456-464.
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Di Kaichang, Li Wei, Yue Zongyu, et al. A machine learning approach to crater detection from topographic data[J]. Advances in Space Research, 2014, 54(11): 2 419-2 429.
DOI:10.1016/j.asr.2014.08.018 URL
Craters are distinctive features on the surfaces of most terrestrial planets. Craters reveal the relative ages of surface units and provide information on surface geology. Extracting craters is one of the fundamental tasks in planetary research. Although many automated crater detection algorithms have been developed to exact craters from image or topographic data, most of them are applicable only in particular regions, and only a few can be widely used, especially in complex surface settings. In this study, we present a machine learning approach to crater detection from topographic data. This approach includes two steps: detecting square regions which contain one crater with the use of a boosting algorithm and delineating the rims of the crater in each square region by local terrain analysis and circular Hough transform. A new variant of Haar-like features (scaled Haar-like features) is proposed and combined with traditional Haar-like features and local binary pattern features to enhance the performance of the classifier. Experimental results with the use of Mars topographic data demonstrate that the developed approach can significantly decrease the false positive detection rate while maintaining a relatively high true positive detection rate even in challenging sites.
[本文引用: 1]
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Bue B D, Stepinski T F.Machine detection of martian impact craters from digital topography Data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45: 265-274.
DOI:10.1109/TGRS.2006.885402 URL
Research on automatic identification of impact craters on Mars and other planetary bodies has concentrated on detecting them from imagery data. We present a novel approach to crater detection that utilizes digital topography data instead of images. Craters are delineated by topographic curvature. Thresholding maps of curvature transforms topographic data into a binary image, from which craters are identified using a combination of segmentation and detection algorithms. We apply our method to a large and technically demanding test site and compare the results to the existing catalog of manually identified craters. Our algorithm finds many small craters not listed in the manual catalog, but it fails to detect heavily degraded craters. A detailed quality assessment of the algorithm is presented. The topography-based crater-detection algorithm offers a relatively simple and ready-to-use tool for identification and characterization of fresh impact craters with an adequate performance for the immediate application to Martian geomorphology
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Hawke B R, Blewett D T, Lucey P G, et al. The origin of lunar crater rays[J]. Icarus, 2004, 170(1):1-16.
DOI:10.1016/j.icarus.2004.02.013 URL
Lunar rays are filamentous, high-albedo deposits occurring radial or subradial to impact craters. The nature and origin of lunar rays have long been the subjects of major controversies. We have determined the origin of selected lunar ray segments utilizing Earth-based spectral and radar data as well as FeO, TiO 2 , and optical maturity maps produced from Clementine UVVIS images. These include rays associated with Tycho, OlbersA, Lichtenberg, and the Messier crater complex. It was found that lunar rays are bright because of compositional contrast with the surrounding terrain, the presence of immature material, or some combination of the two. Mature “compositional” rays such as those exhibited by Lichtenberg crater, are due entirely to the contrast in albedo between ray material containing highlands-rich primary ejecta and the adjacent dark mare surfaces. “Immaturity” rays are bright due to the presence of fresh, high-albedo material. This fresh debris was produced by one or more of the following: (1)the emplacement of immature primary ejecta, (2)the deposition of immature local material from secondary craters, (3)the action of debris surges downrange of secondary clusters, and (4)the presence of immature interior walls of secondary impact craters. Both composition and state-of-maturity play a role in producing a third (“combination”) class of lunar rays. The working distinction between the Eratosthenian and Copernican Systems is that Copernican craters still have visible rays whereas Eratosthenian-aged craters do not. Compositional rays can persist far longer than 1.1Ga, the currently accepted age of the Copernican–Eratosthenian boundary. Hence, the mere presence of rays is not a reliable indication of crater age. The optical maturity parameter should be used to define the Copernican–Eratosthenian boundary. The time required for an immature surface to reach the optical maturity index saturation point could be defined as the Copernican Period.
[本文引用: 1]
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Salamunićcar G, Lončarić S, Grumpe A, et al. Hybrid method for crater detection based on topography reconstruction from optical images and the new LU78287GT catalogue of lunar impact craters[J]. Advances in Space Research, 2014, 53(12): 1 783-1 797.
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Wang Jiao, Cheng Weiming, Zhou Chenghu.A Chang'E-1 global catalog of lunar impact craters[J].Planetary and Space Science, 2015, 112: 42-45.
DOI:10.1016/j.pss.2015.04.012 URL
61Detected lunar impact craters with diameters more than 500m using Chang'E-1 data in a hybrid method.61Compiled a global catalog of 106016 impact craters with comprehensive morphometric parameters.61Inspected the asymmetric spatial distribution of impact craters.
[本文引用: 1]
[73]
Luo Zhongfei, Kang Zhizhong, Liu Xinyi.The automatic extraction and recognition of lunar impact craters fusing CCD images and DEM data of Chang'E-1[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(9): 924-930 .
DOI:10.13485/j.cnki.11-2089.2014.0137 Magsci URL
<p>针对现阶段<span>月球撞击坑<span><span>定量信息提取不足</span></span><span>和误提取的问题</span>,本文提出了一种融合</span><span><span>CCD</span></span><span><span>影像和</span></span><span><span>DEM</span></span><span><span>数据进行<span>撞击坑的自动提取及识别的算法</span></span></span>。<span>(</span><span><span>1</span></span><span><span>)</span></span>在太阳光照下,撞击坑的影像特征满足特定的规律,通过条件匹配在CCD影像中提取撞击坑;(2)<span>在</span><span><span>DEM</span></span><span><span>中,</span></span><span><span>利用撞击坑坑壁点的坡向值的连续性</span></span>,<span>对影像中误提取的撞击坑进行剔除;</span>(3)在DEM中,利用撞击坑边缘点法向量的突变性,<span>提取撞击坑边缘点并进行拟合,计算撞击坑的参数,通过坑底点云所占比例以及剖面线特征识别撞击坑的类型。<span><span>经过&ldquo;嫦娥一号&rdquo;影像与</span></span></span><span><span><span><span>DEM</span></span></span></span><span><span><span><span>数据</span></span></span></span><span><span><span><span>的验证</span></span></span></span><span><span>,<span>该算法在高纬度月球<span><span><span><span>撞击坑分布均匀</span></span></span></span><span><span><span>的区域</span></span></span><span>应用效果较好</span></span></span></span>。</p>
[罗中飞, 康志忠, 刘心怡.融合嫦娥一号CCD影像与DEM数据的月球撞击坑自动提取和识别[J].测绘学报, 2014, 43(9): 924-930.]
DOI:10.13485/j.cnki.11-2089.2014.0137 Magsci URL
<p>针对现阶段<span>月球撞击坑<span><span>定量信息提取不足</span></span><span>和误提取的问题</span>,本文提出了一种融合</span><span><span>CCD</span></span><span><span>影像和</span></span><span><span>DEM</span></span><span><span>数据进行<span>撞击坑的自动提取及识别的算法</span></span></span>。<span>(</span><span><span>1</span></span><span><span>)</span></span>在太阳光照下,撞击坑的影像特征满足特定的规律,通过条件匹配在CCD影像中提取撞击坑;(2)<span>在</span><span><span>DEM</span></span><span><span>中,</span></span><span><span>利用撞击坑坑壁点的坡向值的连续性</span></span>,<span>对影像中误提取的撞击坑进行剔除;</span>(3)在DEM中,利用撞击坑边缘点法向量的突变性,<span>提取撞击坑边缘点并进行拟合,计算撞击坑的参数,通过坑底点云所占比例以及剖面线特征识别撞击坑的类型。<span><span>经过&ldquo;嫦娥一号&rdquo;影像与</span></span></span><span><span><span><span>DEM</span></span></span></span><span><span><span><span>数据</span></span></span></span><span><span><span><span>的验证</span></span></span></span><span><span>,<span>该算法在高纬度月球<span><span><span><span>撞击坑分布均匀</span></span></span></span><span><span><span>的区域</span></span></span><span>应用效果较好</span></span></span></span>。</p>
[本文引用: 1]
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Wood C A, Anderson L.New morphometric data for fresh lunar craters[J]. Lunar and Planetary Science Conference Proceedings, 1978, 9: 3 669-3 689.
URL
Morphometric relations have been determined for 2598 fresh craters on the lunar nearside using data given in the catalog of Wood and Andersson (1978). For each of five principal morphological types, typified by Albategnius C, Biot, Sosigenes, Triesnecker, and Tycho, statistical relations are documented for the following: crater diameter and depth; floor diameter and crater diameter; central peak height and crater diameter; average wall slope and crater depth; central peak occurrence and crater diameter; occurrence of scallops or terraces and crater diameter. The first four relations generally confirm the conclusions of Pike (1977), but the last two differ from results reported by Smith and Sanchez (1973). Small (diameter less than 20 km) flat-floored craters formed in mare terrains are as much as 10% deeper than those formed in the highlands, and the depths of small bowl-shaped craters reflect even greater dependence on terrain. Larger, scalloped-walled craters are deeper in highland terrain than on the maria. Although wall failure does not occur until the crater diameter reaches 13 km, central peaks are found in flat floor craters as small as 2 km.
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Morota T, Furumoto M.Asymmetrical distribution of rayed craters on the Moon[J]. Earth and Planetary Science Letters, 2003, 206(3): 315-323.
DOI:10.1016/S0012-821X(02)01111-1 URL
The synchronous rotation of the satellite ought to cause a spatial variation in the cratering rate over its surface. The crater density is expected to be maximum at the apex of the orbital motion and decrease with the increase of the angular distance from the apex. The ratio of the density at the apex (maximum) to that of the antapex (minimum) depends on the average encounter velocity of impactors to the satellite. Although the Moon is also in a state of the synchronous rotation, it has been supposed that the asymmetry in the crater density on the Moon can be hardly observed. We report here a spatial variation in the density of rayed craters on the Moon, which may be associated with the synchronous rotation. Since the lifetime of a ray is relatively short (<0.8 billion years), the results provide information on recent impacts. Rayed craters are identified on Clementine 750-nm mosaic images. We investigate craters in a lower latitude zone from 42 N to 42 S. To avoid an effect of material difference on the ray preservation, we analyze craters on the highland from 70 to 290 E in east longitude. A total of 222 rayed craters larger than 5 km in diameter are identified in the study area of about 1.4 10 7 km 2 . The average density of rayed craters on the leading side is substantially higher than that on the trailing side. The crater density decreases as a sinusoidal function of the angular distance from the apex. The observed ratio of the density at the apex to that at the antapex is about 1.5. The ratio suggests that recent craters on the Moon are formed mainly by near-Earth asteroids rather than comets with higher encounter velocities.
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Oberbeck V R, Greeley R, Morgan R B, et al. Lunar Rilles: A Catalog and Method of Classification[R]. Space Sciences, 1971:83.
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Li Li, Liu Shaofeng, Wei Wei, et al. Interpretaion of landform of sinuous rilles on the moon based on multidata of remote sensing[J].Remote Sensing for Land and Resources, 2012, 94(3): 16-21 .
[李力, 刘少峰, 韦蔚, . 基于多源遥感数据的弯曲月溪形貌特征解译[J]. 国土资源遥感, 2012, 94(3): 16-21.]
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Fieder G.Lunar Geology[M]. London: Lutterworth Press, 1965.
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Zhou Chenghu, Cheng Weiming, Qian Jinkai, et al. Research on the classification system of digital land geomorphology of 1∶ 1000000 in China[J].Journal of Geo-information Science, 2009, 11(6): 707-724 .
DOI:10.3969/j.issn.1560-8999.2009.06.006 Magsci URL
地貌分类体系是地貌图研制的关键之一,本文在总结国内外地貌及分类研究的基础上,借鉴20世纪80年代的中国1∶100万地貌图制图规范,基于遥感影像、数字高程模型和计算机自动制图等技术条件,归纳总结了数字地貌分类过程中应遵循的几大原则,分析了它们之间的相互关系,讨论了数字地貌分类的各种指标:包括形态、成因、物质组成和年龄等,提出了中国陆地1∶100万数字地貌三等六级七层的数值分类方法,扩展了以多边形图斑反映形态成因类型,以点、线、面图斑共同反映形态结构类型的数字地貌数据组织方式,并详细划分了各成因类型的不同层次、不同级别的地貌类型。中国1∶100万数字地貌分类体系的研究,为遥感等多源数据的陆地地貌解析和制图提供了规范,也为《中华人民共和国地貌图集》的编制奠定了基础,同时为全国大、中比例尺地貌图的分类和编制研究提供了借鉴。
[周成虎, 程维明,钱金凯,. 中国陆地1∶ 100万数字地貌分类体系研究[J]. 地球信息科学学报, 2009, 11(6): 707-724.]
DOI:10.3969/j.issn.1560-8999.2009.06.006 Magsci URL
地貌分类体系是地貌图研制的关键之一,本文在总结国内外地貌及分类研究的基础上,借鉴20世纪80年代的中国1∶100万地貌图制图规范,基于遥感影像、数字高程模型和计算机自动制图等技术条件,归纳总结了数字地貌分类过程中应遵循的几大原则,分析了它们之间的相互关系,讨论了数字地貌分类的各种指标:包括形态、成因、物质组成和年龄等,提出了中国陆地1∶100万数字地貌三等六级七层的数值分类方法,扩展了以多边形图斑反映形态成因类型,以点、线、面图斑共同反映形态结构类型的数字地貌数据组织方式,并详细划分了各成因类型的不同层次、不同级别的地貌类型。中国1∶100万数字地貌分类体系的研究,为遥感等多源数据的陆地地貌解析和制图提供了规范,也为《中华人民共和国地貌图集》的编制奠定了基础,同时为全国大、中比例尺地貌图的分类和编制研究提供了借鉴。
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Stuart-Alexander D E, Howard K A. Lunar maria and circular basins—A review[J]. Icarus, 1970, 12(3): 440-456.
DOI:10.1016/0019-1035(70)90013-8 URL
Lunar Orbiter data make it possible to examine the distribution and relations of maria and large circular basins over the entire Moon. The restricted distribution and age of the maria are in marked contrast to the apparently random distribution in time and place of the circular basins, some of which contain mare fillings. The circular basins are believed to be impact scars, and the maria to be volcanic fills which in each case are younger than the structures they fill. Twenty-nine circular basins 300 km wide or wider are recognized. They are placed in an age sequence because successive stages of degradation can be recognized from the fresh Orientale basin to the almost obliterated basin containing Mare Australe. The maria were emplaced during a short span of lunar history, although some light plains of the highlands may be older maria lightened through age. The present maria are topographically low, tend to be associated with large circular basins, and lie in a crude global belt of regional concentrations; 94% are on the hemisphere facing the Earth. Possible explanations offered for these patterns of mare distribution include impact-induced volcanism, volcanic extrusion to a hydrostatic level, isostatic compensation, lateral heterogeneity in the lunar interior, subcrustal convection, and volcanism due to disruption by Earth's gravity.
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Lucey P G.Mineral maps of the Moon[J].Geophysical Research Letters, 2004, 31(8):1-4.
DOI:10.1029/2003GL019406 URL
Global maps of the distribution of plagioclase, orthopyroxene, clinopyroxene and olivine on the Moon were derived from radiative transfer analysis of 400,000 Clementine UVVIS spectra. Plagioclase inversely correlates with iron while clinopyroxene positively correlates with iron showing these are the major carriers of aluminum and iron respectively. The distribution of olivine in the maria agrees with previous studies; in the highlands the abundance of olivine is low but ubiquitous at a few percent, except within the South Pole-Aitken basin where it is only present in very small exposures. In the very anorthositic farside highlands, olivine is often the sole mafic mineral. The abundance of orthopyroxene is generally low, excepting elevated abundances in the nearside highlands and in areas near and within South Pole-Aitken basin. Mare units with elevated abundances of orthopyroxene are found in some mare and cryptomare deposits distant from the sample return sites.
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Andersson L A, Whitaker E A.NASA Catalogue of Lunar Nomenclature[M]. United States: NASA Reference Publication, 1982.
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Whitaker E A.Mapping and Naming the Moon: A History of Lunar Cartography and Nomenclature[M]. Cambridge: Cambridge University Press, 2003.
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Compiling Committee of the Chang'E-1 Image Atlas of the Moon. The Chang'E-1 Image Atlas of the Moon[M]. Beijing: SinoMaps Press, 2010 .
[《嫦娥一号全月球影像图集》编辑委员会. 嫦娥一号全月球影像图集[M]. 北京:中国地图出版社,2010.]
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Compiling Committee of the Chang'E-1 Topographic Atlas of the Moon. The Chang'E-1 Topographic Atlas of the Moon[M]. Beijing: SinoMaps Press, 2013 .
[《嫦娥一号全月球地形图集》编辑委员会. 嫦娥一号全月球地形图集[M]. 北京:中国地图出版社,2013.]
[本文引用: 2]
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