Article(id=1246843133984658219, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246843131040260216, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-4193.2019.10.006, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1564502400000, receivedDateStr=2019-07-31, revisedDate=1566489600000, revisedDateStr=2019-08-23, acceptedDate=null, acceptedDateStr=null, onlineDate=1775200168367, onlineDateStr=2026-04-03, pubDate=1571932800000, pubDateStr=2019-10-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1775200168367, onlineIssueDateStr=2026-04-03, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1775200168367, creator=13701087609, updateTime=1775200168367, updator=13701087609, issue=Issue{id=1246843131040260216, tenantId=1146029695717560320, journalId=1149651085930835976, year='2019', volume='41', issue='10', pageStart='1', pageEnd='188', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1775200167665, creator=13701087609, updateTime=1775200689635, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1246845320404034096, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246843131040260216, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1246845320404034097, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246843131040260216, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=99, endPage=112, ext={EN=ArticleExt(id=1246843134383117106, articleId=1246843133984658219, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=Advances in marine satellite remote sensing technology in China, columnId=1246843132063670397, journalTitle=Haiyang Xuebao, columnName=Progress on Marine Science and Technology Research over the Past 70 Years in China, runingTitle=null, highlight=null, articleAbstract=

Since the founding of the People´s Republic of China 70 years ago, China has made great achievements in the field of marine satellite remote sensing technology. China has formulated a long-term plan for the development of autonomous ocean satellites, and has constructed three series of ocean satellites, namely, ocean color, ocean dynamic environment and ocean surveillance and monitoring. A ocean space surveillance network dominated by China´s autonomous satellites has been gradually formed, which includes resources and environment monitoring, disaster prevention and mitigation, and safety management. Rationality and other aspects have played an important role. This paper reviews the development of ocean water color and ocean microwave (marine dynamic environment) satellite remote sensing technology in China, emphatically introduces the new achievements in the field of ocean satellite remote sensing technology in China, and prospects the future development of ocean satellite remote sensing technology in China.

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新中国成立70年来,中国在海洋卫星遥感技术领域取得了丰硕成果。中国制定了长远的自主海洋卫星发展规划,构建了海洋水色、海洋动力环境和海洋监视监测三大系列的海洋卫星,逐步形成了以中国自主卫星为主导的海洋空间监测网,在中国海洋资源与环境监测、海洋防灾减灾、海洋安全管理等方面发挥了重要作用。本文回顾了中国在海洋水色、海洋微波(海洋动力环境)卫星遥感技术的发展历程,重点介绍了中国在海洋卫星遥感技术领域所取得的新成果,并对中国海洋卫星遥感技术的未来发展进行了展望。

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林明森(1963—),男,福建省莆田市人,博士,从事海洋遥感、卫星地面资料处理系统建设技术、水色卫星产品处理算法与软件、散射计反演海面风场的反演方法等方面的研究。E-mail:

, authorsList=林明森, 何贤强, 贾永君, 白雁, 叶小敏, 龚芳)}, authors=[Author(id=1248215504335294588, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246843133984658219, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=mslin@mail.nsoas.org.cn.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1248215504503066755, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246843133984658219, authorId=1248215504335294588, language=EN, stringName=Mingsen Lin, firstName=Mingsen, middleName=null, lastName=Lin, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1 National Satellite Ocean Application Service, Beijing 100081, China
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林明森(1963—),男,福建省莆田市人,博士,从事海洋遥感、卫星地面资料处理系统建设技术、水色卫星产品处理算法与软件、散射计反演海面风场的反演方法等方面的研究。E-mail:

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林明森(1963—),男,福建省莆田市人,博士,从事海洋遥感、卫星地面资料处理系统建设技术、水色卫星产品处理算法与软件、散射计反演海面风场的反演方法等方面的研究。E-mail:

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中国海洋卫星遥感技术进展
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林明森 1, 2 , 何贤强 3, 4 , 贾永君 1, 2 , 白雁 3, 4 , 叶小敏 1, 2 , 龚芳 3, 4
海洋学报 | 中国海洋科技研究发展70年 2019,41(10): 99-112
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海洋学报 | 中国海洋科技研究发展70年 2019, 41(10): 99-112
中国海洋卫星遥感技术进展
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林明森1, 2 , 何贤强3, 4, 贾永君1, 2, 白雁3, 4, 叶小敏1, 2, 龚芳3, 4
作者信息
  • 1 国家卫星海洋应用中心,北京 100081
  • 2 自然资源部空间海洋遥感与应用研究重点实验室,北京 100081
  • 3 自然资源部第二海洋研究所,浙江 杭州 310012
  • 4 卫星海洋环境动力学国家重点实验室,浙江 杭州 310012
  • 林明森(1963—),男,福建省莆田市人,博士,从事海洋遥感、卫星地面资料处理系统建设技术、水色卫星产品处理算法与软件、散射计反演海面风场的反演方法等方面的研究。E-mail:

Advances in marine satellite remote sensing technology in China
Mingsen Lin1, 2 , Xianqiang He3, 4, Yongjun Jia1, 2, Yan Bai3, 4, Xiaomin Ye1, 2, Fang Gong3, 4
Affiliations
  • 1 National Satellite Ocean Application Service, Beijing 100081, China
  • 2 Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resources, Beijing 100081, China
  • 3 Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
  • 4 State Key Laboratory of Satellite Ocean Environment Dynamics, Hangzhou 310012, China
出版时间: 2019-10-25 doi: 10.3969/j.issn.0253-4193.2019.10.006
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新中国成立70年来,中国在海洋卫星遥感技术领域取得了丰硕成果。中国制定了长远的自主海洋卫星发展规划,构建了海洋水色、海洋动力环境和海洋监视监测三大系列的海洋卫星,逐步形成了以中国自主卫星为主导的海洋空间监测网,在中国海洋资源与环境监测、海洋防灾减灾、海洋安全管理等方面发挥了重要作用。本文回顾了中国在海洋水色、海洋微波(海洋动力环境)卫星遥感技术的发展历程,重点介绍了中国在海洋卫星遥感技术领域所取得的新成果,并对中国海洋卫星遥感技术的未来发展进行了展望。

海洋卫星  /  海洋遥感  /  水色遥感  /  微波遥感

Since the founding of the People´s Republic of China 70 years ago, China has made great achievements in the field of marine satellite remote sensing technology. China has formulated a long-term plan for the development of autonomous ocean satellites, and has constructed three series of ocean satellites, namely, ocean color, ocean dynamic environment and ocean surveillance and monitoring. A ocean space surveillance network dominated by China´s autonomous satellites has been gradually formed, which includes resources and environment monitoring, disaster prevention and mitigation, and safety management. Rationality and other aspects have played an important role. This paper reviews the development of ocean water color and ocean microwave (marine dynamic environment) satellite remote sensing technology in China, emphatically introduces the new achievements in the field of ocean satellite remote sensing technology in China, and prospects the future development of ocean satellite remote sensing technology in China.

ocean satellite  /  ocean remote sensing  /  water color remote sensing  /  microwave remote sensing
林明森, 何贤强, 贾永君, 白雁, 叶小敏, 龚芳. 中国海洋卫星遥感技术进展. 海洋学报, 2019 , 41 (10) : 99 -112 . DOI: 10.3969/j.issn.0253-4193.2019.10.006
Mingsen Lin, Xianqiang He, Yongjun Jia, Yan Bai, Xiaomin Ye, Fang Gong. Advances in marine satellite remote sensing technology in China[J]. Haiyang Xuebao, 2019 , 41 (10) : 99 -112 . DOI: 10.3969/j.issn.0253-4193.2019.10.006
海洋卫星遥感是利用遥感器对海洋进行远距离非接触观测,具有大范围、全天时、全天候实时成像观测的独特优势,是全球海洋环境监测的重要手段。国际上海洋卫星遥感始于1960年,美国成功发射了世界第一颗气象卫星“泰罗斯–1号”,从约700 km高度的卫星上获得了海表温度场,从而开始了利用卫星资料开展海洋学研究。1978年,美国发射了“雨云–7号” “海洋卫星–1号”两颗卫星,分别利用光学遥感器和微波遥感器实现对全球海洋生态环境和动力环境的卫星观测,从而揭开了海洋卫星遥感的序幕。
中国的海洋遥感技术起步稍晚,20世纪60年代先后开展了机载红外测温仪和机载激光浪高计的研制和海上试验;70年代开始接收美国和日本气象卫星资料应用于海洋气象分析和海冰观测;80年代,中国投入了大量的人力和物力发展海洋遥感技术,并获得了重大技术突破。1980年3月,海洋遥感技术研究被列为“全国遥感技术近期发展规划”重点项目之一。1983年6月,“遥感技术在海洋环境与资源调查中的开发研究”项目列入“六五”国家重点科技攻关计划。1987年1月,王大珩院士、汪德昭院士等26位科学家联名写信给党中央和国务院,提出尽快发展海洋卫星技术。同年10月,国家海洋局、航天部、中国科学院联合完成了《海洋卫星立项研制工作报告》和《海洋卫星技术经济综合论证专题报告》,并上报国务院。自此,中国海洋卫星工作进入基础调研和技术准备阶段。1988年9月7日,中国第一颗带有两个海洋水色通道的气象卫星“风云一号”发射成功。90年代,海洋遥感技术的发展上了一个新台阶。1996年5月,国家海洋局卫星总体部成立,同年12月海洋水色卫星综合技术经济论证通过评审,海洋水色卫星列人国家“九五”卫星发射计划。1997年,在潘德炉院士等努力下,中国成功实现了美国SeaWiFS水色卫星资料的自主接收,为中国海洋遥感技术研究和应用提供了高质量、准实时的卫星资料。2000年11月发布的《中国的航天》白皮书明确了海洋卫星系列是中国长期稳定的卫星对地观测体系的重要组成部分。2001年中国成立了国家卫星海洋应用中心,它是继气象卫星应用中心、资源卫星应用中心之后,中国遥感卫星应用体系建设的又一举措,标志着中国遥感卫星体系天地一体化发展框架的形成。2002年中国发射了第一颗海洋水色卫星(HY-1A),标志着中国海洋遥感技术的发展将跨入一个新阶段,实现了中国海洋卫星的从无到有。2007年4月11日,中国第二颗海洋卫星(HY-1B)成功发射,实现了海洋水色卫星由试验应用型向业务服务型的过渡。2011年8月16日,中国第一颗海洋动力环境卫星(HY-2A)成功发射,卫星主要性能指标达到国际先进水平,填补了中国实时获取海洋动力环境要素的空白。2016年8月10日,以海洋应用为主的“高分三号”卫星在太原卫星发射中心成功发射,填补了中国自主高分辨率多极化合成孔径雷达海洋遥感数据的空白。
本文回顾了新中国成立以来,中国在海洋水色、海洋微波(海洋动力环境)卫星遥感技术的发展历程,重点介绍了中国在海洋卫星遥感技术领域所取得的新成果,最后对中国海洋卫星遥感技术的下一步发展进行了展望分析。
根据总体规划,中国将发展海洋水色卫星、海洋动力环境卫星和海洋监视监测卫星的三大系列海洋卫星,逐步形成以中国为主导的海洋空间监测网。
中国海洋水色卫星的发展起步于20世纪90年代。1997年6月,中国第一颗海洋卫星—“海洋一号A星”(HY-1A)正式立项。该卫星作为试验型业务卫星,采用了CAST968小卫星平台,有效载荷包括1台10谱段海洋水色水温扫描仪(COCTS),以及1台4谱段海岸带成像仪(CZI)。HY-1A卫星运行在798 km的太阳同步轨道上,可实现对中国邻近海域每3 d重复观测的能力,以及境外部分海域的选择性观测。2002年5月15日,HY-1A卫星顺利发射升空,结束了中国没有自主海洋卫星的历史(图1)。HY-1A卫星在轨运行685 d,成像约1 900轨,所获取的连续2年海洋环境数据在海洋资源开发与管理、海洋环境保护与灾害预警、海洋科学研究及国际与地区间海洋合作等多个领域发挥了重要作用,并为中国后续海洋水色卫星研制积累了宝贵经验。
2005年7月,作为中国海洋水色系列卫星的第二颗实验星,HY-1B卫星正式立项。2007年4月11日,HY-1B卫星成功发射(图2)。与HY-1A相同,HY-1B卫星装载1台10谱段海洋水色水温扫描仪(COCTS),以及1台4谱段海岸带成像仪(CZI)。HY-1B/COCTS的成像质量明显好于HY-1A,且观测幅宽增加到3 000 km,实现了对中国邻近海域的每天重复观测;HY-1B/CZI的光谱分辨率(波段带宽)也由HY-1A的80 nm提升至20 nm,可获得更精细的水体物质区分。HY-1B在轨稳定运行了8年10个月,超期服役5年10个月。在轨期间卫星共成像19 233轨,地面应用系统共获取卫星采集的原始数据8.84 TB,生产各级各类数据产品达65.5 TB。HY-1B卫星资料和产品已向海洋管理部门、科研院所、大专院校、业务部门及美国海洋大气局(NOAA)等共50家单位进行了分发应用,累计分发数据量达86.57 TB。HY-1B卫星业务运行期间所获取的海洋遥感数据在海洋资源开发与管理、海洋环境监测与保护、海洋灾害监测与预报、海洋科学研究和国际与地区合作等领域发挥了重要作用,为中国经济发展做出了应有的贡献,发挥了积极作用。
HY-1B卫星2016年停止运行后,中国自主海洋水色卫星资料出现断档问题。因此,在“十三五”期间,中国规划两类专用海洋水色卫星的发展计划,一类是为了尽快解决国产海洋水色卫星资料断档问题而研制的后续业务星HY-1C,另一类是为实现中国国产水色卫星技术性能和应用能力达到国际先进水平而研制的新一代自主海洋水色卫星。2018年9月,HY-1C成功发射,它是中国海洋系列卫星的首颗业务卫星。HY-1C星上装载了10波段海洋水色水温扫描仪COCTS、4波段海岸带成像仪CZI、紫外成像仪、星上定标光谱仪和船舶自动识别系统等5个有效载荷。与HY-1A和HY-1B相比,紫外成像仪、星上定标光谱仪和船舶自动识别系统为新增载荷;COCTS的信噪比大幅提升,可以清晰分辨大洋清洁水体的水色变化;CZI的空间分辨率由HY-1B/CZI的250 m提高到50 m,幅宽由500 km扩展到了1 000 km。在轨测试表明,HY-1C卫星技术状态达到了国际先进水平,使中国成为继美国之后能提供每天全球海洋空间全覆盖海洋水色卫星资料的国家。
除了发展专用海洋水色系列卫星之外,中国在第二代极轨气象卫星“风云三号”(FY-3)系列上也装载了兼具全球海洋水色观测能力的中分辨率成像光谱仪MERSI,并于2008年5月、2010年11月、2013年9月、2017年11月成功发射了FY-3A、FY-3B、FY-3C和FY-3D卫星,提供了丰富的全球海洋水色卫星观测资料。
中国首颗极轨海洋微波(海洋动力环境)卫星HY-2A,于2007年1月获得了国防科工委、财政部的联合批复,并于2011年8月16日发射成功,现仍在轨运行(图3)。卫星轨道为太阳同步轨道,倾角99.34°,降交点地方时为6:00 am,卫星在寿命前期采用重复周期为14 d的回归冻结轨道,高度971 km,周期104.46 min,每天运行(13+11/14)圈;在寿命后期采用重复周期,为168 d的回归轨道,卫星高度973 km,周期104.50 min,每天运行(13+131/168)圈。
HY-2A卫星集主、被动微波遥感器于一体,具有高精度测轨、定轨能力与全天候、全天时、全球探测能力。卫星主要载荷有:雷达高度计、微波散射计、扫描辐射计、校正辐射计。主要使命是监测和调查海洋环境,获得包括海面风场、浪高、海流、海面温度等多种海洋动力环境参数,直接为灾害性海况预警预报提供实测数据,为海洋防灾减灾、海洋权益维护、海洋资源开发、海洋环境保护、海洋科学研究以及国防建设等提供支撑服务[1-3]
HY-2A卫星是中国最为复杂的对地遥感卫星之一,主、被动微波遥感器同时对地观测,电子兼容性复杂,对地天线多达16副,且卫星具有中国遥感卫星中最高精度的测定轨能力,通过采用GPS、多普勒测定轨系统(DORIS)和激光测距3种精密定轨手段,使轨道的确定精度达到厘米量级。虽然,HY-2A卫星是一颗科研业务星,但是,HY-2A卫星的数据产品已经能够满足海洋应用的需要,在台风和海啸的监测中可以做到准确识别,并明显提高海洋灾害预报的时效,具有巨大的应用潜力。
HY-2B卫星是中国第二颗极轨海洋微波(海洋动力环境)卫星,也是中国民用空间基础设施规划的第二颗海洋业务卫星,于2018年10月25日在太原卫星发射中心用长征四号乙运载火箭成功发射(图4)。该星将与后续发射的倾斜轨道海洋动力环境卫星海洋二号C星(HY-2C)和海洋二号D星(HY-2D)组成中国首个海洋动力环境卫星星座。HY-2B卫星配置了雷达高度计、微波散射计、扫描微波辐射计、校正辐射计、数据收集系统(DCS)和船舶自动识别系统(AIS)等6个有效载荷。其中,雷达高度计主要用于测量海面高度、有效波高和重力场等参数;微波散射计用于观测全球海面风场等;扫描微波辐射计用于观测海面温度、海面水汽含量、液态水和降雨强度等参数;校正辐射计用于为雷达高度计提供大气湿对流层路径延迟校正服务;DCS用于接收中国近海及其他海域的浮标测量数据;AIS可为海洋防灾减灾和大洋渔业生产活动等提供服务。HY-2B卫星数据稳定连续、数据精度比HY-2A有明显改善,海面高度、有效波高和海面风场(风速和风向)精度优于国外同类卫星技术水平[4-5],海面温度数据精度接近国外卫星技术水平[6]
中国“高分辨率对地观测系统”(简称“高分专项”)中的“高分三号”卫星(GF-3卫星)是中国第一颗海洋监视监测卫星。2016年8月10日,中国在太原卫星发射中心用长征四号丙运载火箭成功发射GF-3卫星(图5)。GF-3卫星是中国首颗分辨率达到1 m的C频段多极化合成孔径雷达(SAR)卫星。与以往研制的卫星相比,由于该卫星所承担的任务和用途不同,为使其获取更多的信息,采用了全新的体制和多极化的设计,使得卫星可以尽可能把来自于各方面的信息都收集起来,传递给地面,从而为全方位获取地表的4种极化信息提供依据。GF-3卫星是目前世界上分辨率最高的C频段、多极化卫星。同时,GF-3卫星获取的微波图像性能高,不仅可以得到目标的几何信息,还可以定量化反演应用。
GF-3卫星具备12种成像模式,涵盖传统的条带成像模式和扫描成像模式,以及面向海洋应用的波成像模式和全球观测成像模式,是世界上成像模式最多的合成孔径雷达卫星。卫星成像幅宽大,与高空间分辨率优势相结合,既能实现大范围普查,也能详查特定区域,可满足不同用户对不同目标成像的需求。
GF-3卫星显著提升了中国对地遥感观测能力,其提供的可靠、稳定的高分辨率微波图像数据,将极大地满足国内用户对高分辨率民用微波遥感卫星数据的需求。GF-3结束了中国微波遥感数据图像长期依靠外国的历史,不仅可节省大量国家外汇资金,而且为建立中国独立自主的微波遥感数据系统,实现中国各业务领域独立自主的应用和国家海洋安全提供了可靠保证。
自20世纪70年代开始,中国开始了海洋水色遥感技术的研究。由于初期缺乏高辐射灵敏度的专用水色卫星资料,中国学者的研究工作主要集中在利用低信噪比、宽波段的陆地资源卫星、气象卫星资料进行水色要素反演与应用分析,尤其是近海悬浮泥沙的遥感反演。例如:恽才兴等[7]利用Landsat和NOAA遥感数据与同步实测表层水体悬浮泥沙含量,统计分析两者之间的关系,建立线性关系模式来反演泥沙含量;李京[8]利用AVHRR卫星数据与准同步实测泥沙含量,建立两者的关系模型,并利用该模型反演了长江口水域的悬浮泥沙含量;陈夏法[9]利用多期AVHRR遥感数据,研究分析了杭州湾及其附近海域表层悬浮泥沙分布、扩散范围和季节性变化等特征;黎夏[10]建立了悬浮泥沙遥感定量反演的统一模式,并利用该模型反演了珠江口伶仃洋的悬浮泥沙含量;陈楚群等[11]利用Landsat/TM数据对大亚湾水体叶绿素浓度进行了遥感反演;李炎和李京[12]发现海面反射率曲线与遥感器观测反射率曲线之间斜率的传递呈线性关系,从而提出了以斜率传递为基础的悬浮泥沙反演方法。
为发展中国自主的海洋水色卫星资料处理技术,潘德炉和Doerffer[13]分析了中国FY-1B气象卫星在水色遥感方面的应用潜力,发现FY-1B海洋通道资料可以有效地应用于沿海水体悬浮泥沙含量和大洋水体叶绿素浓度的观测,并为中国气象卫星上增加海洋水色通道提供了科学依据。同时,潘德炉等[14]发展了海洋水色卫星辐射模拟仿真技术,实现在卫星发射前模拟卫星入轨后的辐射图像,并可预测卫星图像质量、评价卫星水色资料的利用率和覆盖率,为确保水色卫星发射后资料的有效利用率提供了技术保障。
此外,海洋水色卫星遥感技术发展离不开海水光学特性的现场测量。中国学者在20世纪70年代就开始了水下光学仪器的研发和水体光学特性大范围现场观测。如中国科学院南海海洋研究所自1974年开始连续多年对南海大部分海域进行了水体光学测量,获得了丰富的南海水体光学特性观测资料和科学认识[15]。同时,中国也发展了针对海洋水色遥感建模和真实性检验所需的水体光谱现场测量技术,以及数据分析处理技术[16-18],并自主研发了多波段水下光谱辐射计及海洋光学浮标[19]
随着中国制定了长远的自主海洋水色卫星规划,以及海洋卫星遥感应用需求的强烈牵引下,中国海洋水色卫星遥感技术在21世纪得到了全面发展,逐渐从跟跑进入并跑行列,部分成果达到了国际领跑。
太阳光在大气–水体中的辐射传输是海洋水色卫星遥感的理论基础。中国的海洋水色遥感辐射传输模型研究起步相对较晚,但发展迅速。唐军武等[20]基于蒙特卡罗模拟方法,构建了标量(仅考虑辐射强度,没考虑辐射偏振特性)的水体辐射传输模型,并利用该模型分析了海洋水色卫星遥感关键物理量—离水辐射的方向性分布特征。张鉴等[21]基于矩阵算法,建立了标量的海洋–大气耦合辐射传输模型,并模拟分析了水色遥感参数的变化特性。针对偏振、粗糙海面对水色遥感的显著影响,中国自主建立了考虑辐射偏振、粗糙海面的海洋–大气耦合矢量辐射传输模型PCOART,为中国自主海洋水色卫星资料的精确大气校正打下了基础[22-23]
通常将卫星遥感器接收总辐亮度中去除大气散射、海表反射辐射,提取出真正来自水下的离水辐亮度的处理过程称为大气校正。典型情况下,水色卫星遥感器接收总辐亮度约90%来自大气散射辐射和海面反射,而真正携带水体要素信息的离水辐射只占很小一部分。因此,水色遥感大气校正须从极大的背景噪声中(大气散射、水面反射)提取出微弱的目标信号(离水辐射),具有极大的挑战。因此,精确大气校正是水色卫星遥感的关键技术。
对于大洋或陆架的清洁水体,自Gordon和Wang[24]提出了基于近红外波段的业务化精确大气校正算法框架(简称NIR算法)以来,大洋水体大气校正问题得到了很好解决,并作为业务化算法用于SeaWiFS、MODIS、VIIRS等资料的全球化处理。虽然该算法框架已成熟,但将该算法应用到中国海洋水色卫星,须自主生成算法框架中的大气分子散射、气溶胶散射和大气漫射透过率3类核心查找表。在中国HY-1A卫星阶段,由于缺乏这3类查找表的自主生成技术,大气校正只能采用单次散射近似算法,一定程度上限制了水色信息提取的精度。随着HY-1B及后续水色卫星辐射探测性能的极大提高,单次散射近似算法已不能满足精度要求,需开发考虑多次散射及辐射偏振的精确大气校正算法。基于自主研发的海–气耦合矢量辐射传输模型PCOART,中国突破了3类核心查找表的自主生成技术,构建了自主海洋水色系列卫星的精确大气校正算法[25]。在此基础上,基于考虑地球曲率的海–气耦合矢量辐射传输模型PCOART-SA,生成了适用于大太阳天顶角下的3类核心查找表,为静止轨道水色卫星晨昏观测资料的大气校正打下了基础[26]
近海浑浊水体大气校正一直是国际难题,这是因为受悬浮物强散射作用,近红外波段离水辐亮度相对较大,无法直接利用近红外波段来估算气溶胶信息,导致清洁水体大气校正算法不再适用。为解决该问题,国内外众多学者通过改进现有清洁水体大气校正算法或另辟蹊径来解决浑浊水体的大气校正难题。Pan和Mao等[27]在分析标准SeaWiFS大气校正算法在中国近海存在的问题基础上,提出了一种适用中国近海水体的大气校正算法。丁静等[28]提出将中国近岸浑浊水体进一步区分为中低和中高浑浊水体,用光谱优化方法对中高浑浊水体进行水色大气校正。He等[29]通过分析全球高浑浊河口水体的实测光谱特性,发现由于陆源有机物(黄色物质、有机碎屑)对蓝紫光的强吸收作用,蓝紫光波段离水辐亮度较小,可替代近红外波段进行气溶胶散射估算,从而提出了基于蓝紫光的高浑浊水体大气校正算法(UV-AC),有效解决了近海高浑浊水体的大气校正难题。Mao等[30]基于气溶胶散射光谱满足Angstrom定律的假设,提出了利用现场实测水体光谱库的大气校正算法(ENLF)。He和Chen[31]提出利用短波红外波段来估算近红外两个波段的离水辐射贡献,进一步获得近红外波段的气溶胶散射信息,并应用到标准的近红外大气校正算法中。Chen等[32]基于水体遥感反射率反演误差的光谱经验关系,提出了水体遥感反射率产品数据残差的校正方法,有效降低大气校正结果的不确定性。
定量化的水色要素信息提取是实现海洋水色卫星工程最终应用效果的关键,中国学者在该领域也取得了丰硕的成果。针对水色遥感算法或产品在中国近海的适用性问题,中国学者开展了覆盖渤海、黄海、东海及南海北部的真实性检验[33-36]。同时,开发了适用于中国海域的叶绿素浓度[37]、悬浮物浓度[37-40]等水色要素遥感反演模型。发展了水体吸收、后向散射系数、海水透明度的半分析算法[41-43],以及进一步发展了水体细分组份的遥感模型[44-46]。此外,中国学者亦开展了浮游植物类群和颗粒粒径的遥感反演[47-50],建立了甲藻和硅藻藻华的遥感识别算法[51-52]
除传统的水色要素和水体光学特性反演外,中国学者进一步发展了边缘海复杂水体碳循环关键参数的遥感机理与方法[53]。Bai等[54-55]等利用多个航次数据,建立了基于水色卫星资料的东海表层盐度遥感模型,并反演获得10年序列的夏季长江冲淡水扩散分布。以遥感盐度作为盐淡水混合表征,Bai等[56]提出了适用于复杂边缘海的基于控制因子分析的海水二氧化碳遥感半分析模型。此外,基于水色卫星遥感反演获得的水体表层信息,结合水动力模型、海洋食物网模型,中国学者还发展了边缘海有机碳的储量、侧向输运通量及垂向输出通量的遥感估算模型[57-59]。中国学者发展的海洋碳循环遥感方法体系拓展了水色卫星遥感在海洋生物地球化学领域的应用。
近年来,针对传统极轨水色卫星每天一次观测频率难以满足近海水体环境动态变化及突发海洋灾害实时监测的需求问题,中国学者发展了基于静止轨道的高时间分辨率(逐小时观测)海洋水色卫星遥感技术。率先建立了考虑地球曲率、粗糙海面、偏振的海–气耦合矢量辐射传输模型PCOART-SA,系统研究了静止卫星晨昏时段探测水色的极限能力,构建了适用于晨昏弱光照的大气校正模型[60]。创新发展了静止水色卫星逐时观测资料的协同反演与应用技术,建立了基于静止水色卫星逐时观测资料的近海悬浮物运移、潮汐、余流场、浊度锋面、东海原甲藻藻华和海雾生消等遥感监测技术,开拓了静止水色卫星遥感的新产品[61-63]。自然资源部第二海洋研究所、国家卫星海洋应用中心研究团队2018年研制出了中国首台静止水色卫星遥感器样机,空间分辨率达250 m,并建成了集卫星资料实时接收、自动处理、业务化产品生产和共享服务为一体的静止轨道海洋水色卫星资料处理应用示范系统,实现对西北太平洋海域海洋环境的逐小时观测。
中国海洋微波(动力环境)遥感是随着SZ-4飞船多模态微波遥感器的上天才逐步开展起来,但研究工作大多集中在对国外已有算法模型的引进和模仿上,缺乏自主创新[64-66]。直到2011年8月,中国拥有了自主的海洋动力环境卫星之后,海洋动力环境卫星遥感随之得到了快速发展,在算法模型的研制和应用方面均取得了大量创新性的成果。2018年10月25日HY-2B卫星的成功发射标志着中国海洋动力环境卫星从科研业务星转换到业务星。海洋动力环境要素主要有海面风场、海浪、海流、温度、盐度和深度等。目前上述要素都可以通过遥感手段获取到,并且精度都在逐步提升。
在有效波高的反演算法研究方面,基于二阶理论回波模型,导出了带有偏度系数的二阶理论回波模型[67]。引入了奇异值分解滤波,并根据最大似然估计算法反演参数的不同得到多种重跟踪方案,经比较分析发现4参数模型最适合HY-2A卫星雷达高度计波形反演,有效波高反演精度达到0.31 m。Jiang等[68]重新评估了采用4参数重跟踪算法反演得到的HY-2A卫星雷达高度计有效波高产品,产品精度较3参数重跟踪算法有明显提高。海况偏差是目前雷达高度计海面高度测量中一个非常重要的误差源,国内外学者针对海况偏差提出了很多修正算法,但是就目前而言所有的有效修正算法都是经验模型[69]。在这些经验模型的基础上,近年来发展出了基于神经网络的海况修正算法[70]
卫星遥感获取到的海面风场包括风速和风向两个关键要素,微波散射计、微波辐射计、雷达高度计及合成孔径雷达等载荷都可以获取到海面风速,但微波辐射计、雷达高度计由于观测原理的局限性,不能观测风向。每种载荷在不同的风速区间内的观测精度并不相同[71]。在微波散射计海面风场反演算法方面,利用多解反演算法和二维变分模糊解去除方法对HY-2A卫星散射计数据进行处理,结果表明风速与风向精度均有较大提高。同时,风向模糊解去除能力明显提高,尤其是对台风条件下的风场反演结果,风向反演精度有明显改善。王志雄[72]利用荷兰皇家气象研究所提出了散射计风场多解反演算法(Multiple SolutionScheme,MSS)和二维变分模糊解去除方法(Two-Dimensional Variational AnalysisMethod,2DVAR),应用到HY-2A微波散射计的风场反演中,取得了很好的结果。在雷达高度计海面风速反演方面,王磊等[73]建立了HY-2A雷达高度计的AGC和海面风速的关系,突破性地解决了HY-2A雷达高度计海面风速反演方面的难题。
在海面温度反演算法研究方面,王振占等[74]利用辐射传射方程模拟,建立了海面温度、海面风速、大气水汽含量等海洋环境参数的反演算法。此外,孙广轮等[75]利用最优插值技术发展了网格化的海面温度数据融合方法,拓展了卫星遥感获取的海面温度数据产品。
在海冰密集度反演算法研究方面,石立坚等[76]对典型海区光谱梯度率和极化梯度率进行了统计分析,确定了计算海冰密集度所需的亮温特征值,计算结果与美国冰雪数据中心和德国不来梅大学提供的两种业务化海冰密集度产品一致。河南工业大学[77]发明了算法专利:一种改进的ASI海冰密集度反演算法制造技术,得到的海冰密集度明显低于ASI算法结果,海冰面积减少了15%左右;其中海冰密集度在0.15以上的像元个数比传统ASI算法减少了28.6%左右,显著改善了冰水混合像元海冰密集度反演结果,且有效减弱了天气对高频数据的影响。
卫星遥感器的定标是数据定量化应用的关键。在定标方法的研究方面,张有广和林明森[78]针对卫星雷达高度计后向散射系数和海面高度,总结了海上定标场的分布状况及定标方法。Liu等[79]改进了海面高度绝对定标的方法,在黄海利用实测的验潮仪数据外推到卫星星下点进行海面高度的标定,为雷达高度计的在轨定标提供了一种新的手段。闫龙浩等[80]对GPS浮标测高精度影响因素方面进行了分析,为利用GPS浮标进行海面高度的绝对定标积累了经验。杨磊等[81]总结了国内外卫星高度计定标的主要技术及其发展趋势,对中国自主海上定标场的建设和规划提出了建议。周武等[82]基于微波辐射计的对地观测数据修正了进入冷空反射器的地球信号,建立了地面观测亮温的冷空反射器权重系数矩阵修正冷空观测信号的方法。蒋兴伟等[2]通过对卫星雷达高度计定标方法和定标内容的总结,跟踪调研国际上业务化的高度计定标场的配置,提出中国海洋卫星高度计定标场建设基本思路,同时对定标场周边海区影响高度计定标的地球物理参数和水文气象参数进行初步分析,确定中国海上定标场的基本配置方案,为中国海洋卫星雷达高度计海上定标场建设奠定基础。
在海洋动力环境卫星的精密定轨方面,利用简化动力学方法通过非差状态估计和非差模糊度固定进行参数估计,提高了定轨与定位的精度。在DORIS和激光精密定轨方面,采用动力学方法实现了MOE和POE两种卫星精密定轨的解算。这些定轨方法的应用,使中国海洋动力环境卫星的精密定轨水平达到了世界先进水平[83]
朱俊等[83]研究了一种区别于传统相位观测数据处理的历元间差分处理方法,将相位观测数据转换为距离变化率观测数据,并进行相关误差修正,建立了HY-2卫星的宏表面力和经验力等摄动模型,基于动力学定轨原理实现了基于DORIS相位观测数据的精密定轨;利用HY-2卫星的DORIS实测数据进行定轨,初步计算结果表明,径向轨道误差优于2 cm、三维位置误差约10 cm。蒋兴伟等[2]对HY-2A卫星主要定轨技术之一的DORIS定标技术进行了总结和梳理,并通过SLR检核和独立轨道比较两种方法对DORIS定轨精度进行检验,证明了DORIS精密定轨技术是可以应用到HY-2系列卫星中。同时,林明森等[84]利用HY-2卫星搭载的双频GPS,建立了双频GPS精密定轨技术,经验证后确定使用双频GPS的定轨精度是可以达到要求的,所以在HY-2B卫星系统中,没有搭载DORIS定轨系统,只是用双频GPS进行业务化定轨。并且为后续中国使用北斗系统进行精密定轨奠定了基础。
在HY-2卫星精密定轨的技术基础上,范磊等[85]针对以广播星历为起算轨道的北斗卫星实时滤波精密定轨往往需要较长收敛时间,提出利用超快速精密星历约束的实时精密定轨方法。通过MGEX跟踪网全球分布的51个测站连续7 d的实测数据,利用平方根信息滤波对北斗卫星实时精密轨道进行确定,并以3 d的事后轨道作为参考,评估了北斗卫星实时滤波轨道精度。
中国海洋监视监测卫星—“高分三号”卫星,装载了1 m分辨率的合成孔径雷达,是中国首颗分辨率达到1 m的C频段多极化合成孔径雷达(SAR)成像卫星,在海洋理论与应用领域发挥着越来越重要的作用。对于SAR海洋遥感来说,在一定的雷达参数和轨道条件下,海面的粗糙程度是影响雷达后向散射的主要因素。它所测量的海面粗糙度是由几厘米到几十厘米的表面张力波和短重力波引起的。SAR对海洋学特征或现象(如风、流、海浪、锋面、海面油膜、涡、内波和水下地形等)的成像能力取决于这些特征或现象以各种不同方式改变海面粗糙度的程度。
在海浪信息提取方面,徐延东等[86]发明了算法专利:一种基于同极化SAR数据的海浪参数反演方法,包括获取海面的全极化后向散射系数;利用后向散射系数求得距离向斜率;对距离向斜率快速傅里叶变换(FFT),在频域中除以距离向波数得到表面轮廓频谱;基于距离向斜率谱峰值连线求得海浪传播方向角、主波波长及周期;对表面轮廓频谱进行傅里叶逆变换(IFFT),得到表面轮廓图并计算有效波高;对表面轮廓求方位向偏导得到方位向斜率图;对表面轮廓频谱乘得到z方向速度频谱;对z方向速度频谱进行IFFT得到z方向速度图;利用海浪传播方向角计算xy方向速度等。
在海面风场信息提取方面,张政[87]引入了一个同时包含雷达入射角和海面风速的极化率模型XPR2。通过56幅双极化TS-X和TD-X图像以及与之匹配的ECMWF风场数据拟合出XPR2。再利用38幅HH极化TerraSAR-X图像和与之对应的浮标测量值验证XPR2的有效性。验证的结果显示,采用XPR2反演结果的均方根误差为1.79 m/s,偏差为0.68 m/s。Lin等[88]联合HY-2A散射计和GF-3号C波段SAR风场,提出了台风识别技术,实现了利用中国自主研制的海洋卫星对台风进行精细化观测。
宋小霞等[89]采用欧空局ENVISAT先进合成孔径雷达宽幅模式数据,基于多普勒频移理论模型去除地球和卫星相对运动产生的频移,并用C波段经验模型CDOP(C Band Doppler Frequency)和双尺度辐合散射模型分别去除海面风场和布拉格散射的影响,从而实现高分辨率海表流场的反演。
邹亚荣等[90-91]采用SAR数据,在后向散射系数计算的基础上,从波段、极化方式、入射角等方面开展了海上溢油监测参数分析,并综合溢油形状参数、纹理特征指数、物理特性指数等主要指标,以层次分析法得出每一类指标的权重,对海上溢油遥感监测方法进行了分析,提出了一种SAR数据的多元指标溢油信息提取方法。
从20世纪90年代初开始,根据国外研究机构和院校在SAR目标检测、识别方面的研究成果,并结合机载SAR数据,中国的科研工作者初步展开了对机场、港口、油库、火电站等大型战略目标的检测、识别等研究。
海上目标监测方面,根据SAR图像中最主要的灰度特征,目前常见的主流SAR舰船目标检测方法可分为以下三大类:基于背景杂波统计分布的舰船目标检测、基于极化分解的舰船目标检测和基于极化特征的舰船目标检测。Leng等[92]用核密度估计量来确定目标的空域分布,去除由于一些方位向模糊和杂波像素与船只类似的散射强度导致的目标误检。当其他参数不变,波长较长的系统在斜距向上出现模糊的概率较低,这是因为这些模糊在斜距向上已经超出了目标区域。因此,在SAR图像舰船检测中,Wei等[93]将注意力放在方位向模糊去除当中,并提出了相应的解决办法。Wang等[94]针对高分辨率SAR数据的特点,通过计算船只核密度估计(Kemel Density Estimation,KDE)、船只长宽比和船只像素数目3个特征,根据层次分析法(Analysis Hierarchy Process,AHP)确定特征的权重比例,通过多个特征的优化对初步检测的目标确定其属于船只的置信度,从而得到船只特征的判别阈值,最终得到优化的船只检测结果。刘小楠[95]提出一种信噪比增强方法,该方法能够显著提高SAR图像的信噪比,基于该方法对海上小目标进行监测,得到很好的效果。
李晨波[96]使用SAR探测的海上目标图像数据,检测图像数据中的船只,对船只的特征进行分析,并依据船舶自动识别系统(Automatic Identification System,AIS)提供的匹配信息,确定多种船只的详细信息,去除图像中的假目标,提取船只目标切片,建立测试样本库。提取船只的特征,用提取的船只特征对船只进行分类识别。
中国海洋遥感技术自20世纪60年代开始以来,在几代海洋遥感科研人员的持续努力下,取得了丰硕的成果。中国制定了长远的自主海洋卫星发展规划,发展了海洋水色、海洋动力环境和海洋监视监测三大系列海洋卫星,正逐步形成以中国自主卫星为主导的海洋空间监测网。从2002年发射中国第一颗海洋卫星HY-1A以来,中国至今发射了3颗海洋水色卫星、3颗海洋动力环境卫星(包含中法海洋卫星)、1颗海洋监视监测卫星,实现了全球海洋环境的逐日观测,遥感产品质量也得到极大提升,部分产品已达到国际先进水平,在中国海洋资源与环境监测、海洋防灾减灾、海洋安全管理等方面发挥了重要作用。
伴随着自主海洋卫星发展和卫星资料业务化处理的需求,中国在海洋卫星遥感反演技术方面也取得了全方位的突破。在海洋水色卫星遥感技术方面,中国学者建立了国际领先的海洋水色遥感辐射传输模型,构建了中国自主海洋水色系列卫星的精确大气校正算法;针对中国近海高浑浊水体的特点,提出了多种近海浑浊水体大气校正算法和数据残差矫正方法,有效解决了国际标准算法在中国近海的失效难题;针对水色遥感算法或产品在中国近海的适用性问题,中国学者开展了覆盖中国海域的真实性检验,研发了适用于中国海域的水色遥感反演模型,建立了浮游植物类群、赤潮藻种等一系列创新遥感算法;创新发展了边缘海复杂水体碳循环关键参数的遥感机理与方法,拓展了水色卫星遥感在海洋生物地球化学领域的应用;突破了高时间分辨率静止轨道海洋水色卫星的资料处理与应用技术,将中国海洋卫星遥感监测频率从每天提高到每小时。在海洋动力环境卫星遥感技术方面,针对中国海洋微波(海洋动力环境)卫星设计的特点,提出了中国自主海洋微波(海洋动力环境)卫星有效波高、海面风场等提取算法,并应用到业务化系统中,生产的数据产品精度达到国际领先的水平。针对中国目前还没有海洋微波(海洋动力环境)卫星定标场的现实,提出了利用GPS浮标、验潮仪等的定标方法。针对精密定轨,通过非差状态估计和非差模糊度固定技术,采用简化动力学方法进行参数估计,提高了定轨与定位的精度。在海洋监视监测卫星遥感技术方面,不仅在传统的海洋环境要素提取方面取得了突破,还在海上目标识别方面获得了长足的进步。
当今科技发展日新月异,党的十八大提出了建设海洋强国的战略目标,特别是“一带一路”倡议的实施,为中国海洋卫星遥感发展提供了广阔的空间,也提出更高的要求。通过未来5~10 年的努力,中国的海洋卫星遥感可望在国际上起到引领作用。首先,中国新一代极轨海洋水色卫星HY-1E、HY-1F将在未来5 年内在轨运行,实现对全球海洋水色的高空间分辨率、高光谱分辨率、宽谱段观测。卫星主载荷之一—中分辨率宽谱段成像光谱仪(MWI)已搭载在“天宫二号”空间实验室开展了对海观测实验,成功获得了高质量的海洋水色观测资料和遥感产品[97]。其次,中国正在规划静止轨道海洋卫星,相比于传统极轨海洋卫星,具有逐时甚至分钟级高频连续观测的独特优势,对近海水体动态变化监测、海洋灾害追踪、海上目标监视监测等具有重要作用。中国海洋动力环境卫星将逐步形成组网运行,实现一颗极轨和两颗倾斜轨道海洋动力环境卫星同时在轨运行,满足中尺度及亚中尺度海洋动力现象的监测的需要,完成国际上第一个海洋动力环境星座。此外,在国家重点研发计划的支持下,中国正在大力开展新型海洋光学、微波卫星遥感探测技术的攻关,可望在海洋激光卫星遥感、静止轨道水色卫星遥感、海洋偏振水色卫星遥感、成像宽刈幅雷达测高、海洋盐度遥感、静止轨道合成孔径雷达等方面取得重要突破,将为中国发展国际引领的新型海洋卫星提供关键技术支撑。
考虑到目前的海洋动力环境观测载荷均为传统载荷,海面高度测量仅为星下点观测、海面风速测量范围为2~24 m/s、海面温度测量精度为0.8℃,不能完全满足业务、科学研究等方面的需要,新一代海洋动力环境卫星应该尽快立项,实现宽刈幅海面高度测量、大风速(台风)测量和更高精度的海面温度测量。尽快推动中国海面盐度测量卫星的立项和发射。海面盐度卫星和海洋动力环境卫星联合实现海面温度、海面盐度、海面风场、海浪、表层流场等海洋动力环境要素的观测,为全球气候变化、海气相互作用等研究领域提供有效的科学数据。
  • 国家重点研发计划(2016YFC1401000);国家杰出青年科学基金(41825014);国家自然科学基金(41406207)。
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2019年第41卷第10期
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doi: 10.3969/j.issn.0253-4193.2019.10.006
  • 接收时间:2019-07-31
  • 首发时间:2026-04-03
  • 出版时间:2019-10-25
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出版历史
  • 收稿日期:2019-07-31
  • 修回日期:2019-08-23
基金
国家重点研发计划(2016YFC1401000);国家杰出青年科学基金(41825014);国家自然科学基金(41406207)。
作者信息
    1 国家卫星海洋应用中心,北京 100081
    2 自然资源部空间海洋遥感与应用研究重点实验室,北京 100081
    3 自然资源部第二海洋研究所,浙江 杭州 310012
    4 卫星海洋环境动力学国家重点实验室,浙江 杭州 310012
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https://castjournals.cast.org.cn/joweb/hyxb/CN/10.3969/j.issn.0253-4193.2019.10.006
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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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