Article(id=1249378696969265184, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1249378689566315521, articleNumber=null, orderNo=null, doi=10.3981/j.issn.1000-7857.2025.05.00034, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1746633600000, receivedDateStr=2025-05-08, revisedDate=1769702400000, revisedDateStr=2026-01-30, acceptedDate=null, acceptedDateStr=null, onlineDate=1775804693691, onlineDateStr=2026-04-10, pubDate=1773331200000, pubDateStr=2026-03-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1775804693691, onlineIssueDateStr=2026-04-10, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1775804693691, creator=13701087609, updateTime=1775804693691, updator=13701087609, issue=Issue{id=1249378689566315521, tenantId=1146029695717560320, journalId=1146031591421210625, year='2026', volume='44', issue='5', pageStart='1', pageEnd='124', issueExtLink='null', onlineDate='null', pubDate='1773331200000', pubDateStr='2026-03-13', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1775804691926, creator='13701087609', updateTime=1775804953440, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1249379786603303548, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1249378689566315521, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1249379786603303549, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1249378689566315521, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=39, endPage=56, ext={EN=ArticleExt(id=1249378697518719021, articleId=1249378696969265184, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Advances and reflections on lunar remote sensing spectral exploration, columnId=1150494642224591153, journalTitle=Science & Technology Review, columnName=Exclusive, runingTitle=null, highlight=null, articleAbstract=

The Moon is a key celestial body that records the formation and evolution of the solar system. The composition and characteristics of the lunar surface are the core of planetary science. Visible and near−infrared reflectance specrtroscopy has become the most effective technique for investigating the Moon's surface material composition and characteristics because of its advantages of wide coverage, sensitivity to changes in mineralogy, and minimal environmental impact. It has been widely adopted in many lunar exploration missions both domestically and internationally. In this study, we provided a detailed introduction to the remote sensing spectroscopy payloads and their performance carried by representative lunar exploration missions since the 20th century. We also summarized the scientific achievements of these payloads, covering aspects such as the global iron and titanium content, the composition of the lunar crust and mantle, the content and distribution of lunar surface water, as well as the maturity and optical properties of lunar regolith. Considering the technical features of these payloads and the needs of future scientific research, several development suggestions for future lunar remote sensing spectroscopy were provided including expanding the spectral range of detection, improving the spatial resolution, number of bands, and signal−to−noise ratio of payloads, and developing remote sensing data analysis methods based on "ground truth" of returned samples and artificial intelligence algorithms. These can serve as references for the design of future lunar remote sensing payloads.

, authors=null, authorsList=Dawei LIU, Xin REN, Bin LIU, Rui XU, Xingguo ZENG, Jianjun LIU, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=All rights reserved. Unauthorized reproduction is prohibited., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1249378700505063508, articleId=1249378696969265184, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=月球遥感光谱探测进展及思考, columnId=1150494642375586098, journalTitle=科技导报, columnName=特色专题, runingTitle=null, highlight=null, articleAbstract=

月球是记录太阳系形成与演化历程的关键天体,其表面物质成分与特性是行星科学研究的核心。可见−近红外反射率遥感光谱探测因覆盖范围广、对矿物组成变化敏感且受环境影响小等优势,成为探测月球表面物质组成与特性的最有效技术手段,被多次国内外月球探测任务所采用。介绍了20世纪以来国内外具有代表性的月球探测任务中携带的遥感光谱探测载荷及其性能,总结了基于这些载荷获取的光谱数据所取得的科学成果,涵盖全月铁钛含量、月壳及月幔物质组成、月表水含量及分布、月壤成熟度和光学特性等方面。综合这些载荷的技术特点与后续科学研究需求,提出了月球遥感光谱探测的发展建议:拓展谱段探测范围,提升光谱载荷的空间分辨率、波段数量和信噪比,开发基于返回样品“地面真值”与人工智能算法的遥感数据分析方法。这些建议可为中国未来月球遥感探测载荷的设计提供参考。

, authors=

刘大卫,副研究员,研究方向为月球与行星遥感,电子信箱:

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刘大卫,副研究员,研究方向为月球与行星遥感,电子信箱:

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刘大卫,副研究员,研究方向为月球与行星遥感,电子信箱:

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The Woodlands, Texas: Lunar and Planetary Institute, 2020: 2052., articleTitle=null, refAbstract=null), Reference(id=1249378719417180597, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, doi=null, pmid=null, pmcid=null, year=2024, volume=637, issue=null, pageStart=118737, pageEnd=null, url=null, language=null, rfNumber=[111], rfOrder=110, authorNames=Qian Y Q, Head J, Michalski J, journalName=Earth and Planetary Science Letters, refType=null, unstructuredReference=Qian Y Q, Head J, Michalski J, et al. Long−lasting farside volcanism in the Apollo basin: Chang'e−6 landing site[J]. 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Nature Communications, 2023, 14: 7554., articleTitle=Comprehensive mapping of lunar surface chemistry by adding Chang'e−5 samples with deep learning, refAbstract=null), Reference(id=1249378719559786935, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, doi=null, pmid=null, pmcid=null, year=2022, volume=51, issue=7, pageStart=1317, pageEnd=1337, url=null, language=null, rfNumber=[113], rfOrder=112, authorNames=张良培, 何江, 杨倩倩, journalName=测绘学报, refType=null, unstructuredReference=张良培, 何江, 杨倩倩, . 数据驱动的多源遥感信息融合研究进展[J]. 测绘学报, 2022, 51(7): 1317-1337., articleTitle=数据驱动的多源遥感信息融合研究进展, refAbstract=null)], funds=[Fund(id=1249378706104459507, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, awardId=QYJ−2025−0104, language=CN, fundingSource=中国科学院前沿科学与基础研究局项目(QYJ−2025−0104), fundOrder=null, country=null), Fund(id=1249378706192539895, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, awardId=12373068, language=CN, fundingSource=国家自然科学基金项目(12373068), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1249378700739944542, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, xref=1, ext=[AuthorCompanyExt(id=1249378700748333151, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, companyId=1249378700739944542, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China), AuthorCompanyExt(id=1249378700752527456, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, companyId=1249378700739944542, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1中国科学院国家天文台,北京 100101)]), AuthorCompany(id=1249378700815442020, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, xref=2, ext=[AuthorCompanyExt(id=1249378700819636326, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, companyId=1249378700815442020, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China), AuthorCompanyExt(id=1249378700828024935, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, companyId=1249378700815442020, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2中国科学院上海技术物理研究所,上海 200083)])], figs=[ArticleFig(id=1249378703197806789, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, language=EN, label=null, caption=null, figureFileSmall=P/r/pc0r4yx+m/cmJsRxdw==, figureFileBig=idMyBefSorb+6exxTz4iWw==, tableContent=null), ArticleFig(id=1249378704695173321, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, language=CN, label=图1, caption=中国CE−1 IIM数据反演的Fe、Ti含量全月分布

彩色条带为CE−1 IIM数据覆盖的月表区域。条带中不同颜色

表示月表不同区域反演的(a)Fe和(b)Ti不同的含量。

月海区域Fe、Ti含量明显高于月球高地区域

, figureFileSmall=P/r/pc0r4yx+m/cmJsRxdw==, figureFileBig=idMyBefSorb+6exxTz4iWw==, tableContent=null), ArticleFig(id=1249378704938442955, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, language=EN, label=null, caption=null, figureFileSmall=oFqhYVTve6BzT7AlGDPVTQ==, figureFileBig=IStSGFvlIC6Ky+tvJoYMsQ==, tableContent=null), ArticleFig(id=1249378705047494861, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, language=CN, label=图2, caption=基于M3数据反演的月表水含量分布

水含量分布范围从月表±30°区域的0增加到极区最高约750×10−6

黄色实心点为Apollo探测任务着陆点

, figureFileSmall=oFqhYVTve6BzT7AlGDPVTQ==, figureFileBig=IStSGFvlIC6Ky+tvJoYMsQ==, tableContent=null), ArticleFig(id=1249378705122992337, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, language=EN, label=null, caption=null, figureFileSmall=9BfYO4uLIYazVADPuxsnEw==, figureFileBig=peECAeC3axntwBcELM4bWQ==, tableContent=null), ArticleFig(id=1249378705253015765, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, language=CN, label=图3, caption=CE−4 VNIS原始和包络线去除后光谱数据及物质来源

(a) CE−4 VNIS获取的月表原始光谱反射率曲线。(b) 包络线去除后的CE−4 VNIS光谱曲线,突出光谱曲线的吸收特征。(c)Finsen 撞击坑溅射物在Von Kármán撞击坑内分布,底图为CE−1数字正射影像图(CE−1 DOM)。白色虚线表示Finsen 撞击坑2条主要的东北—西南方向的溅射物条带。白色十字是CE−4着陆点。(d) M3高光谱数据彩色合成图,R:2 μm吸收中心波长,G:2 μm吸收深度,B:1580 nm反射率。 2 μm吸收深度指示镁铁质矿物相对含量。1580 nm的反射率代表月表亮度(受斜长石含量影响)。富含低钙辉石的物质呈浅蓝色,富含高钙辉石的物质呈绿色

, figureFileSmall=9BfYO4uLIYazVADPuxsnEw==, figureFileBig=peECAeC3axntwBcELM4bWQ==, tableContent=null), ArticleFig(id=1249378705366261977, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, language=EN, label=null, caption=null, figureFileSmall=gHKj9uD+qAYxAJzBgG63Ww==, figureFileBig=iVRe22yI0oWByS8QvoH0rw==, tableContent=null), ArticleFig(id=1249378705500479709, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, language=CN, label=图4, caption=月球矿物光谱仪(LMS)在月球表面采集光谱数据示意及CE−5原位光谱数据中2700~3100 nm水吸收特征

(a) 红色标记区域是CE−5 LMS的全景视场。S1、S2、S5是采样点,底图来自CE−5着陆相机。(b) CE−5 LMS 高光谱探测数据在月面的详细探测位置和图像,底图由CE−5 LMS多光谱探测模式获取的180张750 nm图像拼接组成。(c) LMS 高光谱数据在2700~3100 nm波段范围进行包络线去除后的光谱吸收特征。灰色虚线显示接近水(OH)2.85 μm的吸收位置

, figureFileSmall=gHKj9uD+qAYxAJzBgG63Ww==, figureFileBig=iVRe22yI0oWByS8QvoH0rw==, tableContent=null), ArticleFig(id=1249378705601143007, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, language=EN, label=null, caption=null, figureFileSmall=fBRgG9df9KpLtsW3DpAtVQ==, figureFileBig=XbcmyZ+3kTwatNk0ISMoFA==, tableContent=null), ArticleFig(id=1249378705659863265, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, language=CN, label=图5, caption=月壤光度参数(bc)分布

灰色的L形区域代表大多数颗粒的光度参数bc的分布。箭头表示具有不同物理性质的颗粒可能在图中处于不同的位置。反演的月壤

光谱参数(bc)在此图中的投点可以反映月壤的光度特性

, figureFileSmall=fBRgG9df9KpLtsW3DpAtVQ==, figureFileBig=XbcmyZ+3kTwatNk0ISMoFA==, tableContent=null), ArticleFig(id=1249378705760526563, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
任务国家或地区发射
年份/年
探测器波段范围(探测波段)/nm波段数空间分辨率/(m·像素−1
Clementine美国1994UVVIS415、750、900、950、10005100
NIR1100、1250、1500、2000、2600、27006200
SMART−1欧洲2004SIR−1930~2400256310
SELENE日本2007MI可见:415、750、900、 950、1001520
近红外:1000、1050、1250、1550462
SP500~2600300500
Chandrayaan−1印度2008M3目标探测:435~300026070
全球探测:460~297685140/280
LRO美国2009LROC WAC320、360、415、565、605、645、6907385/75
), ArticleFig(id=1249378705856995559, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, language=CN, label=表1, caption=

国际轨道探测任务主要的多光谱/高光谱探测设备性能

, figureFileSmall=null, figureFileBig=null, tableContent=
任务国家或地区发射
年份/年
探测器波段范围(探测波段)/nm波段数空间分辨率/(m·像素−1
Clementine美国1994UVVIS415、750、900、950、10005100
NIR1100、1250、1500、2000、2600、27006200
SMART−1欧洲2004SIR−1930~2400256310
SELENE日本2007MI可见:415、750、900、 950、1001520
近红外:1000、1050、1250、1550462
SP500~2600300500
Chandrayaan−1印度2008M3目标探测:435~300026070
全球探测:460~297685140/280
LRO美国2009LROC WAC320、360、415、565、605、645、6907385/75
), ArticleFig(id=1249378705936687338, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
探测方式任务(发射时间)光谱仪波段范围/nm光谱分辨率空间分辨率或像素数
轨道环绕探测CE−1(2007−10)IIM480~960325.5 cm−1200 m/像素
月表原位探测CE−3/CE−4(2013−12/2018−12)VNISVIS/NIR450~9502~6.5 nm256×256
SWIR900~24003.6~9.6 nm单点光谱测量
CE−5/CE−6(2020−11/2024−05)
LMSVIS480~9502.4~9.4 nm256×256
NIR900~1450单点光谱测量
SWIR1400~23007.6~24.9 nm单点光谱测量
MWIR2200~3200单点光谱测量
), ArticleFig(id=1249378706016379118, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1249378696969265184, language=CN, label=表2, caption=

中国嫦娥系列探测任务光谱仪主要性能

, figureFileSmall=null, figureFileBig=null, tableContent=
探测方式任务(发射时间)光谱仪波段范围/nm光谱分辨率空间分辨率或像素数
轨道环绕探测CE−1(2007−10)IIM480~960325.5 cm−1200 m/像素
月表原位探测CE−3/CE−4(2013−12/2018−12)VNISVIS/NIR450~9502~6.5 nm256×256
SWIR900~24003.6~9.6 nm单点光谱测量
CE−5/CE−6(2020−11/2024−05)
LMSVIS480~9502.4~9.4 nm256×256
NIR900~1450单点光谱测量
SWIR1400~23007.6~24.9 nm单点光谱测量
MWIR2200~3200单点光谱测量
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月球遥感光谱探测进展及思考
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刘大卫 1 , 任鑫 1 , 刘斌 1 , 徐睿 2 , 曾兴国 1 , 刘建军 1
科技导报 | 特色专题 2026,44(5): 39-56
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科技导报 |特色专题 2026 , 44 (5) : 39 -56
月球遥感光谱探测进展及思考
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刘大卫1 , 任鑫1, 刘斌1 , 徐睿2, 曾兴国1, 刘建军1
作者信息
  • 1中国科学院国家天文台,北京 100101
  • 2中国科学院上海技术物理研究所,上海 200083
Advances and reflections on lunar remote sensing spectral exploration
Dawei LIU1 , Xin REN1, Bin LIU1 , Rui XU2, Xingguo ZENG1, Jianjun LIU1
Affiliations
  • 1National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China
  • 2Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
出版时间: 2026-03-13 doi: 10.3981/j.issn.1000-7857.2025.05.00034
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月球是记录太阳系形成与演化历程的关键天体,其表面物质成分与特性是行星科学研究的核心。可见−近红外反射率遥感光谱探测因覆盖范围广、对矿物组成变化敏感且受环境影响小等优势,成为探测月球表面物质组成与特性的最有效技术手段,被多次国内外月球探测任务所采用。介绍了20世纪以来国内外具有代表性的月球探测任务中携带的遥感光谱探测载荷及其性能,总结了基于这些载荷获取的光谱数据所取得的科学成果,涵盖全月铁钛含量、月壳及月幔物质组成、月表水含量及分布、月壤成熟度和光学特性等方面。综合这些载荷的技术特点与后续科学研究需求,提出了月球遥感光谱探测的发展建议:拓展谱段探测范围,提升光谱载荷的空间分辨率、波段数量和信噪比,开发基于返回样品“地面真值”与人工智能算法的遥感数据分析方法。这些建议可为中国未来月球遥感探测载荷的设计提供参考。

月球遥感  /  反射率光谱  /  探测载荷

The Moon is a key celestial body that records the formation and evolution of the solar system. The composition and characteristics of the lunar surface are the core of planetary science. Visible and near−infrared reflectance specrtroscopy has become the most effective technique for investigating the Moon's surface material composition and characteristics because of its advantages of wide coverage, sensitivity to changes in mineralogy, and minimal environmental impact. It has been widely adopted in many lunar exploration missions both domestically and internationally. In this study, we provided a detailed introduction to the remote sensing spectroscopy payloads and their performance carried by representative lunar exploration missions since the 20th century. We also summarized the scientific achievements of these payloads, covering aspects such as the global iron and titanium content, the composition of the lunar crust and mantle, the content and distribution of lunar surface water, as well as the maturity and optical properties of lunar regolith. Considering the technical features of these payloads and the needs of future scientific research, several development suggestions for future lunar remote sensing spectroscopy were provided including expanding the spectral range of detection, improving the spatial resolution, number of bands, and signal−to−noise ratio of payloads, and developing remote sensing data analysis methods based on "ground truth" of returned samples and artificial intelligence algorithms. These can serve as references for the design of future lunar remote sensing payloads.

lunar remote sensing  /  reflectance spectra  /  exploration payload
刘大卫, 任鑫, 刘斌, 徐睿, 曾兴国, 刘建军. 月球遥感光谱探测进展及思考. 科技导报, 2026 , 44 (5) : 39 -56 . DOI: 10.3981/j.issn.1000-7857.2025.05.00034
Dawei LIU, Xin REN, Bin LIU, Rui XU, Xingguo ZENG, Jianjun LIU. Advances and reflections on lunar remote sensing spectral exploration[J]. Science & Technology Review, 2026 , 44 (5) : 39 -56 . DOI: 10.3981/j.issn.1000-7857.2025.05.00034
月球作为地球唯一的天然卫星,在行星科学研究中占据着极其重要的地位。它保存了数十亿年来太阳系内部环境变化的珍贵记录,这一特性使其成为研究太阳系起源、行星形成以及早期宇宙环境的关键对象。相比之下,内行星活跃的地壳活动早已摧毁或掩盖了类似的记录。此外,月球还蕴含着丰富的资源,如氢(H)、氦−3(3He)和钛铁矿等,这些资源不仅为人类建立月球基地提供了重要保障,更是探索深空的重要跳板,能够为火星及其他遥远天体的探索提供生命补给和清洁能源。更为关键的是,月球探测对人类探索宇宙技术的发展起到了重要的推动作用,是人类走向深空的试验场。
人类对月球的探索历程跨越数千年,从古代的神话传说到现代的科学探索,是一段不断突破的壮丽史诗。1609年,伽利略(Galileo Galilei)首次用天文望远镜观测月球,开启了人类科学认识月球的序幕。此后,地基天文观测成为主要手段。20世纪航天技术的飞速发展推动了月球探测进入新阶段。1959年,苏联“月球2号”首次传回月球背面图像;1969年,美国“阿波罗(Apollo)11号”实现人类首次登月,开启了载人探测新时代。Apollo计划带回大量月岩和月壤样品,为研究月球起源和演化提供了直接证据。21世纪,月球探测更加多元化,包括轨道环绕遥感探测、着陆和巡视原位遥感探测及采样返回等。例如,日本2007年发射的“月亮女神”(SELENE)月球环绕遥感探测任务,其目标为获取全月的元素和矿物组成、月球的地形结构、全月的重力场,以及月球的电磁和粒子环境[1]。该探测任务在月表普遍区域成功识别出了纯的斜长岩分布,重新估算了月壳厚度和月背喷发玄武岩的形成年龄,确认了月球磁场异常和微型磁层。印度2008年发射的“月船−1”(Chandrayaan−1)主要的科学目标是基于遥感探测实现高分辨率的月球地质和成分填图[2]。该探测任务绘制了月球极地区域的地图,成功识别和绘制月球水的丰度和分布图,并提供了月球两极裸露水冰的证据。美国的月球勘测环绕器(LRO)于2009年成功发射,其主要科学目标为勘测月表资源和辐射环境[3]。该探测任务发现了月球极地附近存在局部的中子抑制区域,首次揭示了月球上存在高硅质火山岩的直接证据,实现了全月岩石丰度和温度分布的制图。中国的“嫦娥”系列探测任务,不仅实现了月球环绕遥感探测(“嫦娥一号”,CE−1),还完成了月面着陆和巡视原位遥感光谱探测,并通过“嫦娥五号”(CE−5)、“嫦娥六号”(CE−6)探测任务成功实现了月球样品的无人采样返回[4]。“嫦娥”系列探测任务获取了多种类型的全月球及局部区域影像图和地形数据集,准确地刻画了月表形貌特征、地理单元和地质构造;在国际上开创了“微波月亮”研究的先河,并由此得到了全月球表面月壤层的分布及厚度变化;绘制了月表主量元素及镁指数的高分辨率分布图,可广泛应用于月球高地的地壳异质性、寻找高铝玄武岩等方面研究。此外,通过对获取的月表原位遥感探测数据的分析,发现了新型月海玄武岩的存在,揭示了月球深部的物质组成和月壤光度特性,证实了月表水存在形式与含量,并首次实现了对月球背面次表层结构的探测。已开展的这些探测任务从不同角度极大地丰富了人类对月球的认识。
这些探测任务根据科学目标不同,设计并携带了不同用途的科学探测载荷。其中,用于获取月表可见−近红外波段反射光谱特性的多光谱/高光谱探测设备是最常见且几乎必备的载荷。早在Apollo时代,科研人员对月球样品就开展了高精度的可见−近红外高光谱反射率测量,发现所有月球样品的反射光谱都展现出其主要组成矿物的特征吸收,这些吸收特征与晶体场理论预测及地球矿物晶体的透射光测量结果一致[57]。更重要的是,返回样品的实验室光谱与地基望远镜观测的采样区的遥感光谱对比结果也显示,二者的光谱特征基本一致[89]。这些以月球样品作为“地面真值”的比对方法证明了利用可见−近红外反射率光谱特征识别月表主要成分的有效性,奠定了月球反射光谱遥感探测的基础。相比其他探测技术,月表反射率遥感探测覆盖范围广,受环境影响小,能够有效绘制全月尺度的物质成分分布特征。近年来,随着月表着陆和巡视探测技术的发展,特别是以中国“嫦娥”任务为代表的月表原位遥感光谱探测,使得月表遥感探测从全月尺度的千米/百米级向米级/亚米级过渡,与全球探测互补,提供了更加丰富的月面信息。
月球表面的物质成分、分布及其特性是了解月球形成和演化最为直接的记录,也是未来建立月球基地和开展月球原位资源利用的重要基础。月表反射光谱中各吸收特征对应的中心波长、峰型和吸收强度等信息对于月壤与月岩的矿物组成、化学成分和物理状态等性质较为敏感,因而可以用于研究月表物理和成分变化[10]。自20世纪90年代开始,各个国家和地区先后开展的各类型月球探测任务中基本都携带了多光谱/高光谱探测设备对月表的反射光谱进行遥感探测(表1表2)。
1) 克莱门汀探测任务(Clementine)。1969—1976年,美国的Apollo系列探测任务和苏联的月球(Luna)系列探测任务先后成功地将月球样品返回地球,掀起了无人或载人登月的热潮。然而,在此后的将近20年的时间里,对月探测进入了“平静期”。直到20世纪90年代,随着美国Clementine探测任务的成功实施,才打破了近20年的月球探索空白,开启了月球探索的新纪元。
Clementine探测任务于1994年1月25日发射,其设计目的是进入月球轨道并绘制月球表面地图。该任务中搭载了一台紫外可见光相机(UVVIS)和一台近红外相机(NIR)用以实现对月球表面进行多光谱成像,获取月球表面的地质、矿物组成等信息[11]。其中,UVVIS共设计5个波段,分别为415、750、900、950和1000 nm;NIR共设计6个波段,分别为1100、1250、1500、2000、2600和2700 nm。Clementine探测任务共获取了超过280万张月球图像,完成了接近全球范围的多光谱成像,UVVIS和NIR的空间分辨率分别为100、200 m(表1)。
2) 小型先进技术研究任务−1(SMART−1)。欧洲航天局(ESA)的SMART−1任务于2003年9月27日发射,在月球轨道上运行了近2年。该任务携带了一台SIR−1红外光谱仪(SIR)[12],用以实现月表的近红外光谱成像和矿物组成分析。该光谱仪探测范围覆盖930~2400 nm,共256个波段,光谱分辨率为6 nm,最高空间分辨率为310 m。相比于Clementine获取的多光谱数据,SIR能够以更高的光谱分辨率测量完整的月表高光谱数据。
3) SELENOLOGICAL和ENGINEERING探测任务(SELENE)。SELENE探测任务又名KAGUYA探测任务,由日本宇宙航空研究开发机构(JAXA)于2007年9月14日发射。其携带的多/高光谱设备包括一台多波段成像仪(multiband imager,MI)和一台连续光谱测量仪(spectral profiler,SP),用于月表可见近红外反射光谱探测和其表面矿物组成的确定[13]。MI在可见谱段设计有415、750、900、950和1001 nm共5个波段,空间分辨率为20 m;而在近红外谱段设计有1000、1050、1250和1550 nm共4个波段,空间分辨率为62 m。与Clementine的多光谱数据相比,MI具有更高的空间分辨率,能够获取月表小尺度典型地貌的准确光谱特征(如新鲜撞击坑的坑壁和中央峰)。相比于MI,SELENE携带的SP光谱仪在精确解译月表矿物种类和丰度以及化学成分方面更具有优势,它可以测量月表在500~2600 nm波长范围内的约300个波段的高光谱反射率,光谱分辨率为6~8 nm。但其空间分辨率较低,约为500 m。高空间分辨率的MI数据与高光谱分辨SP优势互补,使得SELENE探测任务获取全月表准确的矿物分布成为可能。
4) “月船1号”探测任务(Chandrayaan−1)。“月船1号”是印度空间研究组织(ISRO)的首次行星探测任务,旨在对月球进行遥感观测,以进一步了解月球的起源和演化。“月船1号”于2008年10月22日发射,其携带有一台由美国布朗大学和喷气动力实验室研制的“月球矿物填图”(Moon Mineralogy Mapper, M3)成像光谱仪用于对月球矿物资源及挥发物进行研究。该成像光谱仪在轨工作期间分为全球探测模式和目标探测模式。在目标探测模式下,M3以全空间分辨率和全光谱分辨率进行探测,可以获取260个波段数,光谱覆盖范围为435~3000 nm,光谱分辨率为10 nm,空间分辨率为70 m。在全球探测工作模式下,获取的M3数据有85个波段,光谱探测范围覆盖460~2976 nm,空间分辨率为140 m@轨道高度100 km和280 m@轨道高度200 km。M3全球探测模式数据覆盖了月球95%以上的区域[14]
5) 月球勘测环绕器探测任务。月球勘测环绕器(The lunar reconnaissance orbiter,LRO)由美国国家航空航天局(NASA)于2009年6月18日发射,旨在通过新的空间尺度和新的遥感方法,对月表进行成像,识别未来着落探测任务的安全着陆点并寻找可利用的原位资源[15]。该任务中搭载的成像系统Lunar Reconnaissance Orbiter Camera(LROC)包括2个窄角相机(narrow angle camera, NAC)和1个多光谱宽角相机(multispectral wide angle camera,WAC)。LROC WAC共设计有7个探测波段,分别为用于紫外成像的320、360 nm,以及用于可见光成像415、565、605、645和690 nm波段。这些波段的选择可以用于表征月表常见矿物的光谱特征(如钛铁矿、橄榄石),同时也可与其他探测任务所携带的光谱仪/多光谱成像设备(如Clementine UVVIS和NIR,M3和MI)在探测谱段范围上形成互补,提升对月表物质光谱特征表征的准确性。紫外波段和可见光波段的空间分辨率分别为385、75 m[16]
相比于国外对月遥感探测,中国虽然起步略晚,但极具特色,尤其在原位遥感光谱探测方面取得了突出成就。自2004年中国探月工程正式立项以来,中国仅用20年时间就完成了“绕、落、回”三步走战略。从月表环绕遥感光谱探测到月表着陆和巡视原位遥感光谱探测再到返回样品的实验室光谱探测,中国逐步实现了对月遥感光谱探测从跟跑到并跑再到部分领跑的历史性跨越。
1) “嫦娥一号”(CE−1)探测任务。2007年10月24日,CE−1探测器在西昌卫星发射中心成功发射升空,正式开启了中国月球环绕探测之旅。作为中国探月工程一期的核心任务,其一个重要的科学目标是揭示月球表面物质类型及其分布特征[4,17]。为此,CE−1探测器搭载了一台干涉成像光谱仪(interference imaging spectrometer,IIM),用以获取月表可见近红外光谱特征。该光谱仪基于三角共路干涉的原理,采用推扫式工作模式,在卫星飞行轨道上获取星下点的干涉图,经光谱复原等处理后获取月表的高光谱图像数据[1819]。IIM工作波长范围为480~960 nm,覆盖可见至近红外共32个波段,空间分辨率为200 m,光谱分辨率为325.5 cm−1。在轨工作期间,IIM共采集了覆盖月表约78%区域的高光谱数据,其数据集中于南北纬75o之间[20]
2) “嫦娥三号”(CE−3)和“嫦娥四号”(CE−4)探测任务。中国探月工程二期是以成功实现在月面软着陆,在月表开展原位和巡视探测为目标的探测任务,包括CE−3和CE−4这2次任务[4,17]。CE−3和CE−4分别于2013年12月和2018年12月在西昌卫星发射中心发射,并分别成功着陆于月球正面虹湾区域[21]和月球背面南极−艾特肯盆地内(SPA)的冯·卡门(Von Kármán)撞击坑内[22]。这2次探测任务的巡视器上均搭载了一台可见近红外成像光谱仪(visible and near−infrared imaging spectrometer,VNIS)用于获取月表反射率,进而实现对巡视器巡视路径上的物质组成分析。VNIS采用声光可调滤光器(AOTF)作为分光元件,由可见光/近红外成像光谱通道(VIS/NIR imaging spectrometer)和短波红外光谱通道(SWIR spectrometer)组成。它能够同步获取月球表面目标的全光谱信息。其中,VIS/NIR可获取距离VNIS约0.7~1.3 m处月表在450~950 nm光谱范围内的高光谱图像(256×256像素),而SWIR则可获取对应于VIS/NIR图像采集范围内900~2400 nm谱段范围的单点高光谱数据。VIS/NIR和SWIR的光谱分辨率分别为2~6.5 nm和3.6~9.6 nm[23]。CE−3、CE−4搭载的VNIS在国际上首次实现了月球表面原位遥感光谱探测,为研究月表物质组成和特性提供了全新的视角。这一创新性成果不仅填补了国际上月表原位遥感光谱探测的空白,也标志着中国在月球探测技术领域取得了重大突破。
3) “嫦娥五号”(CE−5)和“嫦娥六号”(CE−6)探测任务。中国探月工程三期是以成功实现月球样品自动取样并安全返“回”地球为目标的探测任务,包括CE−5和CE−6这2次任务[4,17]。CE−5和CE−6分别于2020年11月和2024年5月于文昌航天发射场发射,并分别成功着陆于月球正面风暴洋的吕姆克山脉以北地区[24]和SPA内Apollo盆地的南部[25]
这2次探测任务的着陆器上均搭载了一台月球矿物光谱分析仪(lunar mineralogical spectrometer,LMS)用于获取采样区域物质矿物组成及H2O/OH分布特征,为采集的样品提供地质背景信息。LMS仍然沿用了与CE−3/4 VNIS一样的AOTF的分光方式,能够对月表在480~950 nm波长范围进行高光谱成像(256×256像素),以及获取成像区域所对应的900~3200 nm波段范围内的一条单点高光谱数据。LMS由4个通道组成,包括可见成像光谱通道(480~950 nm)(VIS)、近红外光谱通道(900~1450 nm)(NIR)、短波红外光谱通道(1400~2300 nm)(SWIR)和中波红外光谱通道(2200~3200 nm)(MWIR)。其中,VIS和NIR光谱通道的光谱分辨率为2.4~9.4 nm,SWIR和MWIR光谱通道的分辨率为7.6~24.9 nm[26]。此外,与CE−3/4 VNIS不同的是,LMS除了具备专为对采样点探测前后进行精细高光谱探测的全谱段探测模式外,还具备采样区域的全视场多光谱扫描模式,用于对整个采样区域进行多光谱探测[27]。CE−5/6 LMS在国际上首次获取了采样区域的原位光谱数据,通过与采样区轨道遥感光谱和返回样品的实验室光谱的比对,不仅可以为样品分析提供详细的地质背景支撑,同时也能够修正遥感探测的不确定性,作为桥梁和纽带,将返回样品的实验室分析结果从局部小尺度拓展到全月尺度。
从以上的分析可以看出,国内外历次对月遥感探测任务所搭载的光谱类载荷在设计上并不相同,且各具特点(表1表2)。例如,Clementine UVVIS/NIR和SELENE MI轨道遥感探测都以多光谱探测模式为主,而Chandrayaan−1 M3和CE−1 IIM等轨道遥感探测则以高光谱探测为主。相比于多光谱探测载荷,高光谱探测载荷可以获取月表连续完整的光谱曲线特征,更有利于对月表物质的准确识别和反演。但多光谱遥感探测通常采用滤光片进行分光,这种方式带宽较宽,数据信噪比较高,而以M3为代表的轨道高光谱探测载荷通常采用光栅分光技术。光栅分光能够在一次测量中同时获取所需高光谱各个波段的数据,适用于如M3这种采用快速推扫成像方式对月进行高光谱探测的光谱仪。中国CE−1 IIM轨道光谱仪则采用傅里叶变换方式进行分光。其优点是可以根据需要计算探测谱段范围内任意波长处的反射率数据[18],但这也导致光谱仪结构相对复杂,包含移动干涉部件,抗震性能较差。
与轨道遥感光谱探测不同,中国CE−3/4/5/6月球原位遥感光谱探测任务在国际上首次采用了AOTF进行分光。AOTF通过改变射频信号的频率实现波长的快速扫描,驱动射频的频率对应分光波长。与采用傅里叶分光的干涉成像光谱仪相比,AOTF分光技术具有全固态、无需机械结构、环境适应性较强的优势,可靠度较高,特别适用于月表原位这种凝视型平台观测[23,28]。相比于光栅分光,尽管AOTF各谱段数据为分时获取,总扫描时间略长,但其每一波段曝光积分时间均可调,可实现大动态范围信号的探测,探测灵敏度更高[28]
尽管CE−3/4/5/6任务所携带的光谱仪采用了相同的分光方式,但与CE−3/4 VNIS相比,CE−5/6 LMS工作波长范围向长波方向进行了拓展(从2400 nm拓展至3200 nm),部分覆盖了H2O/OH约3 μm吸收所对应的波长范围,可以更好地实现对月表水的探测。同时,向长波方向拓展也使得对月表反射光谱在约2 μm吸收特征的刻画更加完整,有助于对月表准确物质组成的判别。为实现该目的,LMS在VNIS的CMOS探测器+InGaAs探测器的基础上,额外增加了HgCdTe的MCT探测器以提升LMS在2200~3200 nm探测数据的信噪比(InGaAs最多可外延至约2500 nm使用)[26]
在阿波罗时代,人类对月球的认知主要依赖于月球样品分析,存在区域局限性和过度外推的局限性。近30年来,随着以上介绍的轨道遥感和月表原位遥感等探测任务获取的可见近红外光谱数据的不断积累,为研究月球提供了全新的视角。
1) 月表主要物质组成与分布。(1) 全月Fe、Ti含量。自1994年Clementine探测任务成功实施以来,人类对月表物质成分的识别及其分布特征的了解不断加深,其中最具里程碑意义的成果是首次获取了全月表Fe、Ti含量的空间分布。Lucey等[2930]和Blewett等[31]通过分析Clementine UVVIS探测器获取的Apollo采样点的多光谱数据,结合对应区域返回样品的Fe和Ti实测含量,构建了基于750 nm反射率与950 nm/750 nm反射率比值反演月表Fe含量、基于750 nm反射率与415/750 nm反射率比值反演Ti含量的算法。将该算法应用于Clementine UVVIS数据,成功绘制出人类首幅全月Fe、Ti元素分布图。后续探测的其他任务,如SELENE的MI[3233]及中国的CE−1 IIM[20]均基于Lucey等[2930]和Blewett等[31]的方法框架,开发了适用于自身探测器数据的Fe、Ti含量的算法,并绘制了全月的Fe、Ti含量分布图(图1[20])。这些不同探测器获取的全月的Fe、Ti含量分布从多源角度证明了月球的整体成分与地球地幔的成分不同,排除了地球和月球具有相同成分的月球起源模型假说(如分裂说和共聚说)。同时,月球正面月海、背面高地,以及SPA盆地在Fe、Ti含量上的显著差异也揭示了月球地质多样性[29,34]。此外,通过对月海玄武岩区域的Fe、Ti含量分析,完成了对月表不同成分的月海单元划分。结合这些月海单元的撞击坑定年分析结果,为研究月球后期热演化历史奠定了基础[3537]
(2) 月壳物质组成。早在20世纪六七十年代,通过对返回月球样品的研究,科研人员便提出了月球岩浆洋假说(lunar magma ocean,LMO)用以解释月球早期的岩浆演化过程[38]。该假说推断随着月球原始岩浆的演化,如橄榄石、低钙辉石等较重的镁铁质矿物结晶下沉形成月幔,而较轻的斜长石组分上浮形成月壳。然而,由于采集的月球样品的空间局限性,月壳,特别是高地月壳,是否真的如该假说所述主要由纯的斜长岩组成仍然缺乏全球性的证据支持。该问题直到SELENE MI和Chandrayaan−1 M3获取了全月遥感光谱数据后才得以解决。对MI和M3的可见近红外反射光谱的分析结果显示,全月广泛分布着以1.25 μm独特光谱吸收特征为代表的纯的斜长岩富集区域(斜长石含量可达98%以上)[3940],证明了全月范围内纯斜长岩的广泛存在,支持了岩浆洋假说。对月表大型撞击盆地及其中央峰的多源遥感反射光谱(clementine,MI,M3)的分析发现,月壳在垂向上存在着矿物成分变化,从富含长石的上月壳逐渐向镁铁质矿物增多的下月壳过渡。这些镁铁质矿物主要包括低钙辉石(如斜方辉石)、橄榄石和Mg质尖晶石等[4144]。它们很可能在月壳深处共存,以位于斜长岩月壳底部的层状镁铁质侵入体的形式存在[45]
(3) 月海玄武岩矿物组成。月海玄武岩不仅因其独特的平滑形态、光学图像上较暗的色调与其他月表物质明显不同,其在可见近红外波段的反射率光谱也展现出明显的以辉石960~1000 nm和2100~2300 nm的特征吸收为主的光谱特征。与大多数月球高地含辉石的物质相比(吸收中心920~950 nm、1800~2100 nm),月海中辉石的吸收中心更加偏长波方向,表明月海玄武岩中辉石的平均钙含量明显更高[41],主要以单斜辉石为主(包括普通辉石和易变辉石)。尽管辉石主导了大多数月海玄武岩的遥感光谱特征,但其他矿物(如斜长石、橄榄石、钛铁矿)也在月海玄武岩中存在,且当其含量升高时,也会对月海玄武岩整体的光谱特征产生影响[46]。例如,轨道高光谱遥感数据显示,相比于古老的月海玄武岩覆盖区域,年轻的月海玄武岩区域的吸收中心向更加偏长波方向(>1000 nm、>2200 nm),2 μm吸收深度明显减弱,且1 μm吸收变宽[4749]。先前的研究将这种光谱特征变化归因于年轻月海玄武岩覆盖区域内的橄榄石含量明显增加[47,5051]。而对CE−5样品的分析结果则显示,月海年轻玄武岩这种光谱特征的变化主要是由其组成的辉石更加富Fe所引起的,而非橄榄石含量增多[52]
(4) 月幔主要矿物组成。长期以来关于月幔的物质组成仍然是一个待解决的问题。随着全月轨道遥感光谱数据的不断积累,为研究月幔主要物质组成问题提供了一定的线索和启示。Yamamoto等[53]对SELENE SP获取的全月光谱数据分析发现,橄榄石广泛出露于Imbrium、Moscoviense等撞击盆地周围的同心圆区域。探测到的橄榄石很可能是这些大型撞击盆地形成时所挖掘并抛射在撞击盆地周围的月幔物质。然而,一些对SPA盆地光谱特征的研究却并不支持该结论。SPA是整个月球上最大和最古老的撞击构造,根据撞击模型理论,该撞击事件应该挖穿了月壳并将深部的上月幔物质暴露在月表[54]。对该区域的遥感光谱数据的分析结果显示,除了在SPA外部区域的Schrdinger盆地和Zeeman撞击坑发现一些局部橄榄石出露外[55],SPA盆地的表面并没有发现橄榄石的广泛分布。相反,SPA表面的反射率光谱特征与低钙辉石的光谱特征更为接近[5659]。因此,人们推测月幔物质很可能以低钙辉石为主导[54,60]
2) H2O/OH轨道遥感光谱探测。早在20世纪六七十年代对Apollo样品的分析显示月球是极度“干燥”的。然而,Clementine探测任务利用雷达技术在月球极区永久阴影区内探测到了可能存在水冰的信号[61],再次掀起了对月球H2O/OH探索的热情。反射光谱技术是探测月球水的一种最为直接的方式。H2O/OH在反射光谱3 μm处具有明显的吸收特征,通过分析H2O/OH在3 μm附近的遥感反射率光谱,可以识别月表的H2O/OH并分析其含量。Pieters等[62]对M3获取的高光谱数据分析发现,月表广泛的区域都存在H2O/OH在3 μm的吸收特征,证实了月表H2O/OH的存在。此外,该吸收特征随纬度的增加而增强,也与太阳光照环境有关,暗示着H2O/OH的太阳风成因。基于一种新的热校正模型和月表水反演模型,Li等[63]利用M3数据构建了全球首张月表H2O/OH含量分布图,并发现H2O/OH的含量的确随纬度增加而升高,接近(500~700)×10−6图2[63])。进一步的分析发现,对于一些月球火山碎屑沉积物覆盖区域,其近红外反射光谱显示出与富含H2O/OH物质一致的光谱吸收特征。暗示着探测到的部分H2O/OH也很可能源自月球内部[64]。更为重要的是,对M3数据的分析确认了月球永久阴影区存在着1.3、1.5、2.0 μm水冰的特征吸收,这为月球极区存在水提供了最为直接的证据[65]
3) 太空风化和月壤光学成熟度。月球由于缺乏大气层和全球性磁场,表面月壤长期受到微陨石撞击和太阳风粒子轰击,导致其发生一系列物理和化学变化,这种现象被称为月球的太空风化。由于太空风化作用,月壤的粒径逐渐减小,形成黏结集块岩(agglutinate),并在月壤颗粒表面或内部生成粒径从几纳米到几微米的单质铁(纳米相单质铁npFe0和微米相单质铁mpFe0)。研究人员据此提出了成熟度(maturity)的概念,用于描述月壤积累太空风化产物的程度[66]。单质铁的积累不仅反映了月壤成熟度的变化,还显著改变了月壤的光谱特征,表现为光谱吸收减弱、反射率随波长增加而上升(reddening)及反射率幅值降低[67]。实验室中,人们常用Is/FeO来定量描述月壤的成熟度。其中,Is为测量的月壤的铁磁共振强度,其与月壤中的npFe0含量具有非常好的线性相关性[68],FeO为对应月壤中的二价铁含量。
在遥感光谱应用中,Lucey等[69]结合Clementine的UVVIS多光谱数据,首次提出了基于光谱参数计算月壤光学成熟度指数(OMAT)的概念。OMAT通过750 nm反射率和950、750 nm反射率比值来量化月表成熟度的光谱效应。其受月表物质组成的影响较小,能够在一定程度上指示月壤的相对暴露时间,为月表定年提供参考。此外,一些研究则利用可见近红外光谱遥感数据直接计算npFe0和mpFe0含量,定量表达太空风化强度。例如,Trang等[70]基于SELENE MI多光谱数据,通过辐射传输模型解混,获得了全月npFe0和mpFe0含量分布,为深入研究月壤的太空风化奠定了基础。
1) 月表物质组成。Ling等[71]对CE−3 VNIS获取的着陆点附近月壤的光谱数据分析发现,CE−3着陆区为一个新型玄武岩覆盖区域,其主要由富含Fe、Ca的辉石和富Fe的橄榄石组成,但以往的Apollo和Luna采样任务从未采集到这种类型的玄武岩,并推断其源岩很可能形成于岩浆洋分异的晚期。后续基于对CE−3 VNIS数据的辐射传输模型反演、光谱比对也都进一步证实了该结果[7273]。这些研究深化了人们对月球晚期火山活动的认识。
除了对月球正面的玄武岩覆盖区域进行原位探测,中国对月球背面的原位遥感光谱探测同样取得了令人瞩目的成果。Li等[74]利用修正高斯模型,基于CE−4 VNIS获取的月球背面SPA Von Kármán撞击坑内的前两月昼的原位光谱数据,证明了CE−4着陆区物质成分明显不同于月球正面的月海玄武岩,富含低钙辉石和橄榄石。这种矿物组合很可能代表了月球深部物质。进一步与轨道遥感数据的比对结果显示,CE−4 VNIS探测到的物质是由着陆区东北方向芬森撞击坑挖掘并抛射到Von Kármán撞击坑表面(图3[74])。该研究引发了研究人员对CE−4着陆区物质成分的广泛关注和多角度探讨[7579]。例如,基于CE−4 VNIS获取的巡视路径上更多的原位光谱数据,Gou等[80]根据光谱吸收位置和波段面积比等光谱参数,发现CE−4月壤中橄榄石与低钙辉石的比值较高,推断该区域的物质很可能是源自深部的月幔物质。而Lin等[77]利用基于Apollo样品构建的月表物质成分光谱反演经验模型,发现CE−4月壤中低钙辉石含量高于橄榄石,且含有大量的斜长石,认为这种矿物组合可能为含橄榄石的苏长岩(olivine−norite),它们可能源自下月壳或者是源于由撞击作用产生的一个巨大的熔融池的结晶分异。作为月球上最大的撞击构造,SPA盆地是研究月球深部物质(下月壳、上月幔)的天然窗口,这些基于CE−4 VNIS的光谱分析为解译SPA的物质组成及来源提供了重要的约束条件。
此外,“玉兔二号”月球车在CE−4着陆区域进行巡视探测时,在一个小坑内部及附近发现了具有特殊光泽的神秘胶状物质。通过对这些胶状物质的VNIS原位光谱数据的分析,Lin等[81]和Gou等[82]发现这些胶状物与Apollo样品中的撞击角砾岩相似,其特殊的光泽与其含有较高含量的撞击玻璃物质有关。通过进一步对VNIS数据的辐射传输模型解混,Yang等[83]提出这些胶状物中混有碳质小行星撞击体的残余物质。这是碳质球粒陨石残余物首次在月球表面被原位光谱探测技术所发现,为了解月球表面的撞击过程和月壤演化提供了证据。
2) H2O/OH原位遥感光谱探测。经过几十年的轨道遥感探测和对返回月球样品的分析,各种证据均让人们相信月球上有水的存在。但月球有多少水、是什么形式,以及来自哪里一直存在争议。目前认为月球“水”的来源主要包括:太阳风粒子与月表物质相互作用产生的羟基物质;月球原生(内部)水;撞击月球的彗星或陨石带来的水和含羟基物质。Liu等[84]通过对CE−5 LMS获取的光谱数据分析后发现,CE−5着陆区月壤中明显地含有以羟基形式存在的水(图4[84]),但平均含量较低。对CE−5月球样品进一步的实验室X射线衍射、拉曼光谱和电子探针分析结果显示,CE−5样品中至少存在一种含水矿物——羟基磷灰石,其含量不均匀,折合月壤样品羟基水的含量从0 到179×10−6不等[84]。作为月球岩浆结晶的重要产物,羟基磷灰石的发现证明了CE−5月壤样品中存在来自月球内部、岩浆结晶过程的“水”。除了CE−5月球样品,对Apollo任务返回的月球玄武岩样品的实验室分析结果同样也证明了组成月球玄武岩的羟基磷灰石中“水”的存在[8587]。这说明了“水”在月球晚期岩浆活动过程中不仅存在,而且可能起到了非常重要的作用。此外,Liu等[84]指出,CE−5样品中较低的胶结玻璃(agglutinitic glass)含量也表明太阳风注入对CE−5月壤中水的产生贡献较小。这是因为对月球样品的实验室分析发现,太阳风注入产生的水主要存在于月壤的胶结玻璃中,而其含量是衡量太阳风对月表水贡献的一个重要指标[88]
然而,Lin等[89]对CE−5 LMS获取的月壤和岩石的光谱分析则认为,CE−5着陆区的水应以太阳风注入贡献为主,提出以下2方面的证据支持:(1) 相较于受着陆器羽流扰动而暴露出的浅表层月壤,未被羽流扰动区域的、太空风化程度更高、太阳风注入影响更大的表层细粒月壤,其水含量明显升高,证明了太阳风注入对月壤中水含量的重要影响;(2) 着陆区的岩石相比于月壤展现出更强的H2O/OH吸收特征(约180 ×10−6vs.约120×10−6)。岩石中大部分水(约2/3)应与月壤一样与太阳风注入产生的水有关,而多出的少部分(约1/3)的“水”可能是岩石中源自月球内部的内生“水”。对CE−5月壤颗粒氘/氢比值的离子探针分析结果似乎也支持CE−5月壤中“水”主要以太阳风贡献为主[90]
这2项基于月表原位光谱探测的成果为研究月球水开辟了新视角,其原位探测结果为轨道遥感探测数据中水信号的解译和估算提供了新的月面真值。
3) 月壤光度特性及成熟度。月壤的光度特性反映了其在不同光照和观测条件下的反射、散射和吸收特性。研究月壤光度特性对了解月壤的物理特性,以及校正不同光照几何条件下的遥感反射率光谱至关重要。尽管科学家已在实验室中对月壤样品进行过光度特性测试[9192],但由于采样过程中的扰动,这些样品无法反映月壤在月表的真实状态。虽然轨道器遥感数据可用于推断月壤光度特性[9394],但其通常难以实现对月面同一目标的多角度连续观测。相比之下,中国月表原位光谱探测为研究月壤光度特性提供了宝贵机会。目前,已开展了多项研究利用Hapke辐射传输模型对中国月表原位光谱数据进行解译,从而了解月壤的光度特性。假设颗粒的大小远远大于波长,且颗粒之间紧密排列,Hapke[95]构建了用于描述和预测光线在粗糙、颗粒状天体表面(如月球、火星土壤)反射行为的物理模型。该模型模拟月表反射率的要素包括:观测几何角度、表示单颗粒月壤散射光能力的单次反照率(主要由介质物质组成决定)、描述月壤颗粒间的多次散射函数项(为单次反照率的函数)、描述单个颗粒将光散射到不同方向偏好特性的相函数(包括Henyey−Greenstein和Legendre 2种形式)、描述阴影遮蔽效应的函数项(shadow hiding opposition effects, SHOE),以及描述月壤颗粒反射率在零相位角附近剧烈激增的相干后向散射冲效应函数项(coherent backscattering opposition effects, CBOE)。在利用Hapke辐射传输模型对月表光度特性进行推断时,往往假设探测区域的物质成分是相同的。因此,各部分具有一致的颗粒单次反照率而不是不同位置处单次反照率发生变化。此外,考虑到SHOE和CBOE效应只在非常小的相角下才会较为明显[95],且月表原位探测的相角往往较大,在实际应用中常将此2项对月壤反射率的贡献忽略。经此简化,获取的月壤多角度反射率只与探测的光照几何、月壤组成颗粒的单次反照率,以及描述月壤颗粒相函数的光度参数有关。因此,在已知光照几何的条件下,可以利用多角度探测数据反演月表光度参数。例如,基于CE−4着陆区月壤的VNIS多角度光谱数据,Lin等[96]对Hapke辐射传输模型相函数(Henyey−Greenstein)中的光度参数(bc)的反演结果表明,CE−4着陆区月壤与Apollo月壤样品光度特性较为一致,均表现出前向散射的特性。Yang等[97]采用Legendre相函数对CE−4 VNIS数据进行光度参数的反演结果也得到相同结论。Guo等[98]和Xu等[99]对CE−5着陆区月壤的光度参数同样进行了反演。结果显示,CE−5月壤颗粒不规则且其内部散射体密度较低(图5[98])。相比于CE−4月壤,CE−5月壤表现出更加明显的前向散射特征,这可能是因为CE−5着陆区与CE−4着陆区的月壤在物质组成及空间风化程度上的差异所引起[98]。值得关注的是,CE−4和CE−5原位光谱探测均表现出月壤前向散射的特性,而轨道遥感测量则显示月壤为后向散射[94]。这种差异可能源于数据的不同探测尺度:原位分析对月壤单个颗粒的光度特性更加敏感,而轨道遥感探测则对颗粒集合体的光度特性更为敏感[98]
此外,月表原位光谱探测数据也为了解着陆区/巡视区月壤成熟度、暴露历史等方面提供了重要的信息。利用 VNIS月表原位光谱数据,Wang等[100]基于Hapke辐射传输模型估算CE−3月壤中的npFe0含量约为0.368%,对应于Is/FeO约为53的亚成熟月壤。而受着陆器下降过程中羽流影响的区域,npFe0含量约为0.217%,说明火箭喷射冲击所移除的物质比留在原地的月壤风化程度更高。这也暗示着最表层月壤与下部月壤在成熟度上存在差异。通过对CE−3、CE−4和CE−5着陆区的月表原位光谱数据的比较分析,Wu等[101]发现CE−5和CE−3着陆点的月壤成熟度低于CE−4着陆点的月壤。该研究还显示CE−5着陆区表层月壤与厘米深度处的下层月壤表现出相似的成熟度,表明尽管该区域CE−5地质年龄较年轻,但其表面物质的翻耕作用非常迅速。结合原位光谱数据和CE−5样品的实验室分析,Lu等[102]发现CE−5着陆区月壤的Is/FeO约为66。同时,月表原位光谱、轨道遥感光谱以及样品实验室光谱的综合分析结果表明,CE−5月壤中含有大量大粒径的mpFe0。它们可能是源自月球晚期玄武岩本身或者由过饱和的单质铁在极度富FeO(>17%)的玄武岩中聚集而成[103106]。富含FeO的玄武岩在空间风化作用下会生成粒径更大且生成速率更快的单质铁颗粒[102]。围绕月壤成熟度开展的原位光谱分析,深化了对月壤中单质金属铁生长机制的理解,为研究不同成分月壤的差异性太空风化作用奠定了基础。
近20多年来,随着“嫦娥”系列探测任务的顺利实施,中国对月遥感光谱探测取得了举世瞩目的成就,得到了国际月球科学界的高度关注。中国对月遥感探测技术从轨道遥感光谱探测起步,逐步迈向月表原位遥感光谱探测,探测谱段范围不断拓展,波段数量不断增加,空间分辨率从全月尺度的百米级向区域原位探测的分米/厘米级迈进。对月探索研究也逐渐从基于单一轨道探测数据的观测结果,向原位探测、轨道探测和样品实验室联合观测的多维度结果转变。积累的多源遥感光谱数据,虽然使得我们得以重新审视月球,但也为对月遥感光谱探测带来了新的挑战。
1) 探得更“宽”。当前,国内外对月遥感光谱探测载荷的探测谱段多集中在350~2500 nm,然而这一范围在识别月表物质组成时存在局限。月壤主要组成矿物辉石、长石和橄榄石的特征吸收在此谱段内相互叠加(如辉石和橄榄石在约1 μm处的吸收,橄榄石与长石在约1.25 μm处的吸收),这给利用该谱段光谱数据进行月表矿物的准确识别和含量估算带来困难。此外,该波段范围也不利于准确判断月表水的存在形式(H2O还是OH)及其含量。尽管CE−5/6 LMS将光谱探测范围扩展至3200 nm,但仍未覆盖与水吸收相关的完整波段范围,影响对月表水吸收中心及吸收强度的准确识别。
未来对月遥感光谱探测应将光谱载荷的探测谱段范围设计得更宽,涵盖可见近红外谱段的同时,尽量向中波红外乃至远红外谱段拓展。虽然辉石、橄榄石、长石的特征吸收在350~2500 nm谱段相互叠加,但它们在约8 μm处的以Christiansen feature(CF)为代表的光谱特征却差异明显[107]。通过计算遥感光谱在中波约8 μm处的CF值,可更好地区分月表不同区域的矿物组成。对于月表水探测,将谱段范围拓展至中远红外,不仅可以获取完整的月表在约3 μm的吸收特征,还可通过对约6 μm处光谱数据的分析了解月表水的存在形式。约6 μm处的光谱特征仅与分子水相关,而羟基水在此谱段并无明显光谱特征。Honniball等[108]正是基于对这一波段范围的遥感光谱数据分析,确认了月表高纬度地区存在水分子。
中远红外光谱探测可作为可见近红外探测波段的有效补充,联合分析两者的数据,将提升对月表物质成分识别的准确性。但其也面临着诸多技术挑战。在中远红外探测谱段,任何高于绝对零度的物体自身的热辐射远高于太阳光照射于物体上被反射的辐射能量。对于该谱段的探测,光机系统本身的热辐射已经是不可忽视的干扰源,甚至会淹没有效的探测信号。因此中远红外成像光谱探测系统需考虑如何实现低温光学以抑制背景辐射的影响。为解决此问题,可以考虑在将探测器集成于真空杜瓦的前提下,配合利用深空低温环境对光机进行被动的辐射制冷,抑或是利用斯特林高效制冷系统对光机系统进行主动制冷,以实现抑制系统的背景辐射。另外,信噪比优化也是中远红外光谱探测的重要挑战。由于诸如月球这样的深空探测目标往往信号较弱,为了提高信噪比,一方面,可以采用高性能的低温探测器(如主要成分为HgCdTe的MCT探测器)来降低噪声水平;另一方面,可以通过合理的光学系统设计,如采用大口径望远镜和高效的光谱仪有效提高信噪比。值得期待的是,中国“嫦娥七号”(CE−7)探测任务轨道器搭载了一台宽谱段红外成像光谱分析仪,其光谱探测范围覆盖可见近红外及中波红外(0.45~10 μm)[109]。随着未来CE−7探测任务的成功实施,其获取的全月遥感光谱数据将为深入了解月表物质组成及水的含量和分布提供更为直接准确的信息。
2) 探得更“细”。探得更“细”可分为宏观上探的更“细”和微观上探的更“细”。宏观上的“细”主要对轨道遥感光谱探测而言。目前,月球轨道器遥感探测在可见近红外波段面临的问题是,难以同时实现高空间分辨率和足够的波段数量,导致无法兼顾获取探测目标详细的地质背景信息与准确的光谱特征,特别是无法感知一些细微的月表光谱特征的变化。例如,Kaguya MI的空间分辨率最高达20 m,但仅有9个波段,而Chandrayaan−1 M3的全球模式波段数量虽然达81个,但空间分辨率仅约200 m。此外,光谱仪的信噪比也严重制约着对月表的探测能力。例如,月球永久阴影区的光照条件较弱,但这些区域可能存在的丰富水冰资源却是未来遥感探测重点关注的对象。此时,提升光谱仪的信噪比,以适应弱光或微光条件下的光谱探测,显得尤为关键。因此,中国未来轨道遥感光谱探测应着重提升载荷的空间分辨率、波段数量及信噪比。一个值得借鉴的案例是美国最近的Lunar Trailblazer mission探测任务搭载的high−resolution volatiles and minerals Moon mapper (HVM3) 光谱仪。HVM3是M3的升级版,其科学目标包括:一是在探测到水信号的基础上,进一步区分观测到的吸收特征是由分子水、水冰还是羟基所致;二是确定永久阴影区域是否存在水冰。HVM3光谱探测范围为600~3600 nm, 光谱采样间隔为10 nm(约300个波段)。相比于M3,HVM3更高的空间分辨率和更多的谱段数量能够有效地识别和区分月表水的状态。此外,HVM3能够利用地形散射的太阳光探测永久阴影区内的水冰信号,对永久阴影区的探测信噪比大于50,而对月表中纬度区域则可大于200,灵敏度显著提升[110]。但需要指出的是,成像光谱系统的信噪比与谱段数、空间分辨率在设计上是相互制约的。谱段数的增多意味着采样间隔的降低,导致单像元可接收到目标光谱辐射能量也随着信号带宽减少。同时,在推扫成像光谱系统中,高空间分辨率意味单次曝光允许的驻留时间降低,制约可设计的积分时间,进而影响可接收到目标的光谱辐射能量。谱段数和空间分辨率的提高都会对探测的信噪比形成制约。对高性能成像光谱系统可以通过像移补偿的方式提升单位观测视场的驻留时间,补偿信噪比,但这样也会使得成像系统在每个视场停留的时间更长,从而增加成像系统完成一次完整扫描所花费的总时间。因此,在进行探测器设计时,也需要结合轨道探测任务的实际情况和规划,进行多参数权衡设计,形成最优的设计方案。
微观层面的“精细”探测主要针对原位遥感光谱探测。中国CE−3、CE−4、CE−5、CE−6探测任务所搭载的光谱仪虽已实现月表原位光谱探测,但其数据的空间分辨率仍然有限(分米/亚米级)。此外,无论是VNIS还是LMS仅能在约450~950 nm波段范围内对月面进行成像,长波方向只能获取单点光谱数据。因此,中国未来月表原位光谱探测应致力于实现更高空间分辨率(如毫米级)和中长波成像(>950 nm)的发展目标。这不仅能够提供更为详细的月面信息,例如月壤的粗糙度、颗粒大小及形状,还能获取更精细尺度下的月面矿物组成及分布信息。这将极大地提升对月壤演化历史的认知,并更好地服务于月表采样位置的精准选取。
3) 探得更“真”。在实验室内对月球样品物质组成和高精度光谱的准确测量是月球遥感光谱探测的基础。这些测量结果可作为“地面真值”,用于校准和验证遥感仪器的观测数据。此外,基于月球样品建立的月表物质成分遥感光谱反演模型是将实验室测量结果拓展至全月范围的重要工具。然而,目前的遥感光谱模型大多基于Apollo和Luna任务采集的月球样品,这些样品主要来自月球正面低纬度区域,空间代表性有限,可能导致遥感光谱模型实际应用中估算结果与实测值存在显著偏差。例如,早期对月球年轻玄武岩区域的轨道遥感光谱分析认为其主要矿物为橄榄石,但对CE−5样品的分析显示,该区域矿物成分应以富铁高钙辉石为主[52]。这种差异源于富铁高钙辉石与橄榄石光谱特征相近,而Apollo和Luna任务返回的样品中鲜有以富铁高钙辉石为主的样品,导致遥感光谱被误判为富含橄榄石。此外,CE−6月壤样品的化学分析显示其TiO2质量分数为2.7%[25],而遥感光谱推断的TiO2质量分数约为6%[111],二者存在明显偏差。
与Apollo和Luna样品均采自低纬度区域不同,中国CE−5和CE−6采集的样品均来自月球中纬度区域,其中CE−6更是首次获取了月球背面的样品。这些样品在矿物和化学组成上与Apollo和Luna样品存在显著差异[2425],极大地丰富了月球样品的多样性。这些来自全新区域的样品为优化和更新现有的遥感光谱反演模型提供了宝贵机遇。未来建立遥感光谱反演模型时,应涵盖CE−5和CE−6样品的信息。这些新的“地面真值”也将显著提升利用遥感光谱数据反演月表物质成分的准确性。
4) 探得更“智”。近年来,人工智能逐渐成为月球遥感光谱数据解译的重要技术手段。与传统的经验、半经验、理论以及基于光谱参数的月表物质成分光谱反演模型相比,人工智能能够捕捉遥感反射率光谱中难以察觉的细节变化。例如,Yang等[112]基于返回月球样品的化学组成和采样位置的轨道遥感光谱数据,建立了一种基于一维卷积神经网络的(1D CNN)月表成分含量反演方法。结果显示,与传统方法相比,1D CNN的反演结果精度更高。每个像素的光谱数据本身可以被视为一个一维序列。而1D CNN非常适合处理像光谱这样的序列数据。它能自动学习光谱波段之间的局部关系(相邻波段的相关性),提取局部特征,从而有效捕捉光谱曲线在吸收位置、吸收深度等方面细微的特征变化,而这些特征往往与特定矿物或元素含量紧密相关。此外,由于返回月球样品的稀缺性,也可以将迁移学习的方法用于月表物质成分的反演。例如,首先利用地球矿物的光谱数据库(如USGS光谱库)中的数据进行预训练模型的建立。然后将预训练模型迁移到月球数据上,利用少量的、可以作为“地面真值的”月球样本对模型进行微调,以使其更加适应月球特定的环境(空间风化、独特矿物组合等),显著降低对月球样本数量的依赖,提升模型在小样本条件下的泛化能力和精度。
此外,近几十年的月球遥感探测积累了海量的轨道、月表原位遥感光谱以及返回样品的实验室光谱数据。然而,这些数据目前分散且未充分整合,限制了其在月球科学研究中的深度应用。利用人工智能可以实现多源、多分辨率遥感光谱数据的充分融合,提高月球遥感光谱探测的精度和效率,使月球遥感探测更加智能化。例如,可以使用诸如深度神经网络(DNN)、长短期记忆神经网络(LSTM)等方法[113]实现月球原位/实验室光谱数据与轨道遥感数据的点−面数据融合,获取高精度、大范围、空间连续的探测数据,为月球科学研究和未来的资源开发提供有力支持。
  • 中国科学院前沿科学与基础研究局项目(QYJ−2025−0104)
  • 国家自然科学基金项目(12373068)
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doi: 10.3981/j.issn.1000-7857.2025.05.00034
  • 接收时间:2025-05-08
  • 首发时间:2026-04-10
  • 出版时间:2026-03-13
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  • 收稿日期:2025-05-08
  • 修回日期:2026-01-30
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中国科学院前沿科学与基础研究局项目(QYJ−2025−0104)
国家自然科学基金项目(12373068)
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    1中国科学院国家天文台,北京 100101
    2中国科学院上海技术物理研究所,上海 200083
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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