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遥感技术与应用  2021, Vol. 36 Issue (1): 11-24    DOI: 10.11873/j.issn.1004-0323.2021.1.0011
综述     
“全球生态系统碳循环关键参数立体观测与反演”项目概述与研究进展
刘良云1,4(),白雁2,孙睿3,4,牛振国1,4
1.中国科学院空天信息创新研究院,北京 100094
2.自然资源部第二海洋研究所,杭州 310012
3.北京师范大学地理科学学部遥感科学与工程研究院,北京 100875
4.遥感科学国家重点实验室,北京 100101
Stereo Observation and Inversion of the Key Parameters of Global Carbon Cycle: Project Overview and Mid-Term Progressess
Liangyun Liu1,4(),Yan Bai2,Rui Sun3,4,Zhenguo Niu1,4
1.Aerospace Information Research Institute,China Academy of Sciences,Beijing 100094,China
2.ndInstitute of Oceanography,State Oceanic Administration of China,Hangzhou 310012,China
3.Beijing Normal University,Stereo Observation and Retrieval of Key Parameters of Global Ecosystem Carbon Cycle,Beijing 100875,China
4.State Key Laboratory of Remote Sensing Science,Beijing 100101,China
 全文: PDF(4746 KB)   HTML
摘要:

准确评估全球碳循环是准确估算未来大气CO2浓度、预测气候变化的关键。目前全球陆地与海洋碳源汇估算时空不确定性大。除碳循环模式理论和认知存在缺陷外,全球尺度上缺乏精细时空分辨率的生态系统碳循环参数观测数据是造成全球碳循环估算存在巨大不确定性的重要原因之一。为此,项目以立体观测为技术手段,通过协同全球台站观测资料和多源卫星遥感数据,研制要素齐全的高质量陆地与海洋生态系统碳循环关键参数产品(GLOCC),不仅包括主要碳源汇直接观测产品,如陆地生态系统生产力、生物量、土壤碳库和海水二氧化碳分压、海水颗粒有机碳等;还包括陆地与海洋生态系统光合作用关键参数以及碳循环模型过程关键变量。项目执行3 a多来,收集与处理了1981~2019年来的28种国内外卫星数据和19种全球碳循环产品生产相关的全球遥感产品,攻克了多源卫星遥感数据的一致性处理关键技术,发展了陆地与海洋生态系统碳循环关键参数的高精度卫星反演关键技术,初步研制了GLOCC碳参数产品生产与共享平台,并通过集成国内外卫星遥感数据,将部分陆地生态系统碳参数的时间分辨率从8 d提高到5 d。目前已经有7个GLOCC产品在国内外多个数据中心提供了产品共享服务。项目预期能够为全球变化研究提供时空分辨率高、时间序列长、碳循环参数全的遥感产品,并服务于全球碳源汇准确估算需求,并提供全球和区域碳收支的重要科学数据。

关键词: 碳循环全球变化遥感地球观测立体观测大数据    
Abstract:

Accurate assessment of global carbon sequestration is the key step to accurately assess future CO2 concentrations and predict climate change. At present, the spatial and temporal uncertainties of global terrestrial and oceanic carbon sinks are very large. Although the model simulation method is widely used in global carbon source/ sink research, many studies have pointed out that the simulation results varied greatly. Besides the deficiencies in carbon cycle models, the lack of global observational data on fine spatiotemporal resolution is also a most important cause of global uncertainties in carbon cycle estimation. Therefore, the project aims to develop comprehensive, top-level, and long time-series Global Land & Ocean Carbon Cycle (GLOCC) datasets using multi-source earth observation data, and to explore new methods to directly estimate global carbon sequestration, such big data. The GLOCC datasets not only include products directly related to carbon sources and sinks, such as terrestrial ecosystem productivity, forest biomass, soil carbon pool and seawater carbon dioxide partial pressure, seawater particulate organic carbon, etc; it also includes key driven variables of carbon cycle process models for both terrestrial and ocean ecosystems. Over the past three years, we have collected and processed 28 domestic and foreign satellite data and 19 carbon-related global remote sensing products 1981 to 2019, and have developed a series of algorithms for processing of multi-source satellite data. We have also developed the inversion models for the 24 GLOCC products, in which the temporal resolution of some GLOCC parameters was improved from 8 days to 5 days by integrating domestic and foreign satellite remote sensing data. So far, 7 GLOCC products were freely available in multiple data centers. The project will benefit the global change research community by long-term global products with fine spatial and temporal resolution, and to provide new discoveries on global carbon sequestration.

Key words: Carbon cycle    Global changes    Remote sensing    Earth observations    Stereoscopic observation    Big data
收稿日期: 2020-08-17 出版日期: 2021-04-13
ZTFLH:  P237  
基金资助: 国家重点研发计划项目(2017YFA0603000);国家杰出青年科学基金项目(41825002)
作者简介: 刘良云(1976-),男,湖南邵阳人,研究员,主要从事植被定量遥感研究。E?mail: liuly@radi.ac.cn
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引用本文:

刘良云,白雁,孙睿,牛振国. “全球生态系统碳循环关键参数立体观测与反演”项目概述与研究进展[J]. 遥感技术与应用, 2021, 36(1): 11-24.

Liangyun Liu,Yan Bai,Rui Sun,Zhenguo Niu. Stereo Observation and Inversion of the Key Parameters of Global Carbon Cycle: Project Overview and Mid-Term Progressess. Remote Sensing Technology and Application, 2021, 36(1): 11-24.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2021.1.0011        http://www.rsta.ac.cn/CN/Y2021/V36/I1/11

图1  碳循环关键参数产品及其对碳源汇估算贡献关系图
图2  TanSat叶绿素荧光卫星遥感反演产品(2018年3、7、9、12月的月均值合成)
图3  亚洲边缘海海洋参数2003~2014年变化
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