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星载近红外高光谱CO2遥感进展
引用本文:毕研盟,王倩,杨忠东,谷松岩,吴荣华,刘成保. 星载近红外高光谱CO2遥感进展[J]. 中国光学, 2015, 8(5): 725-735. DOI: 10.3788/CO.20150805.0725
作者姓名:毕研盟  王倩  杨忠东  谷松岩  吴荣华  刘成保
作者单位:国家卫星气象中心, 北京 100081
基金项目:国家高技术研究发展计划(863计划)资助项目(No.2011AA12A104)
摘    要:在应用需求的拉动和高光谱技术发展的驱动下,利用被动式星载近红外高分辨率光谱仪探测大气CO2分子柱含量已成为一个相当活跃的研究领域。本文介绍了卫星遥感CO2在科学和社会发展方面的基本需求,分析了被动遥感CO2的优势和不足;对国际上最新的以美国OCO-2(2014年7月发射)和日本GOSAT(2009年1月发射)为代表的专项CO2遥感任务进行了综述,包括仪器指标、观测模式和定标模式等方面;着重对OCO-2定标精度需求和多种在轨定标方式进行了阐述;从应用和数据处理角度,简要比较了光栅和傅里叶干涉探测技术探测CO2的主要特点;最后对定量反演原理进行了概述,并对这一领域的未来发展进行了展望。

关 键 词:高光谱  CO2  遥感  定量反演
收稿时间:2015-03-11

Advances on space-based hyper spectral remote sensing for atmospheric CO2 in near infrared band
BI Yan-meng,WANG Qian,YANG Zhong-dong,GU Song-yan,WU Rong-hua,LIU Cheng-bao. Advances on space-based hyper spectral remote sensing for atmospheric CO2 in near infrared band[J]. Chinese Optics, 2015, 8(5): 725-735. DOI: 10.3788/CO.20150805.0725
Authors:BI Yan-meng  WANG Qian  YANG Zhong-dong  GU Song-yan  WU Rong-hua  LIU Cheng-bao
Affiliation:National Satellite Meteorological Center, Beijing 100081, China
Abstract:Driven by application requirements and the development of hyper spectral technology, atmospheric total column CO2 monitoring using passive space borne high resolution spectrometry has become a very active research field. In this paper, we introduce the requirements for satellite observation of CO2 in scientific and social development, and analyze the advantages and disadvantages of space-based CO2 measurement, and provide an overview of the research mission and progress of the latest international Orbiting Carbon Observatory-2(OCO-2, launched by NASA in July 2014) and Greenhouse Gases Observing Satellite(GOSAT,launched in January 2009), including instrument specifications, observing modes, calibration modes, and especially focus on the requirement accuracy of calibration and several kinds of in-orbit calibration modes. From the perspective of application and data processing, CO2 detection technology between grating and Fourier transform method for interference are briefly compared. In addition, the quantitative inversion principle and future development of this field are also presented at the end of this paper.
Keywords:hyper spectral  CO2  remote sensing  quantitative inversion
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