基于超光谱热红外数据的一氧化碳反演通道选择
投稿时间:2020-04-16  修订日期:2020-05-15  点此下载全文
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张贝贝 中国科学院空天信息创新研究院 定量遥感信息技术重点实验室 bbzhang0@126.com 
王宁 中国科学院空天信息创新研究院 定量遥感信息技术重点实验室 wangning@aoe.ac.cn 
姚微源 中国科学院空天信息创新研究院 定量遥感信息技术重点实验室 yaowy@aircas.ac.cn 
钱永刚 中国科学院空天信息创新研究院 定量遥感信息技术重点实验室  
马灵玲 中国科学院空天信息创新研究院 定量遥感信息技术重点实验室  
李传荣 中国科学院空天信息创新研究院 定量遥感信息技术重点实验室  
唐伶俐 中国科学院空天信息创新研究院 定量遥感信息技术重点实验室  
刘耀开 中国科学院空天信息创新研究院 定量遥感信息技术重点实验室  
高彩霞 中国科学院空天信息创新研究院 定量遥感信息技术重点实验室  
基金项目:国家重点研发专项(2016YFB0500602);自然科学基金(41601398,6170011903);中科院大科学项目“全球遥感定标基准网”(181811KYSB20160040);中科院先导项目(XDA13030402)
中文摘要:一氧化碳(CO)在热红外波段吸收强度弱且吸收区内具有较多的干扰信号,利用热红外数据反演高精度CO廓线的难度大。超光谱红外探测仪的开发和应用,为提升CO廓线的反演精度提供了可能。然而,随着超光谱热红外数据分辨率的上升、通道之间的间隔变窄,这在给数据引入特有可反演信息的同时产生大量冗余信息。为了保证反演精度和效率,有必要对通道进行选择来获取包含最大可反演信息的通道同时剔除冗余信息。本文提出了一种同时考虑通道灵敏度和权函数特性的峰采样通道选择方法,用于从超光谱红外数据中反演CO廓线。该方法首先通过分析通道对不同气体的灵敏度情况,去除受其他气体干扰较大的通道获得初选通道。然后,分析初选通道的权函数特性后发现,位于CO亮温变化谱线中峰顶和峰底的通道分别包含了不同大气层的CO反演信息,将这些通道选取为最终通道选择结果。以阿拉善沙漠地区、京津地区、长江三角洲及珠江三角洲的冬夏晴空大气为主要研究对象,比较峰采样法与最优灵敏度剖面法(OSP)所得的通道选择结果及相应的CO廓线反演精度。结果表明,该方法选择的通道比OSP方法选择的通道能覆盖更宽的光谱范围且包含更多的CO反演信息。而且,峰采样通道选择方法的应用可以有效提高本文所研究区域和季节的CO廓线反演精度,其中在阿拉善地区冬季大气条件下改善效果最为明显,反演结果的均方根误差(RMSE)由3.23×10-8 g/g降至3.07×10-8 g/g,平均反演精度提高了10.56%。
中文关键词:通道选择  CO廓线反演  超光谱热红外数据  灵敏度  权函数特性
 
Channel selection for carbon monoxide retrievals based on ultra-spectral thermal infrared data
Abstract:As the weak absorption intensity and high interference signals in the thermal infrared band of carbon monoxide (CO), it is difficult to retrieve CO profiles with promising accuracy from thermal infrared data. The development and application of ultra-spectral infrared detector make it possible to improve the retrieval accuracy of CO profile. However, the ultra-spectral resolution and the huge channel numbers of the data not only enhance the abundant atmospheric retrieval information, but also induce lots of redundant information. As such, it is necessary to do the channel selection to ensure the accuracy and efficiency of retrieval. In this paper, a channel selection method considering both channel sensitivity and weighting function characteristics is proposed for CO profile retrieval from ultra-spectral infrared data. First, by analyzing the gas sensitivity of the channels in CO absorption band, the channels severely affected by other gases are excluded and initial channel group is obtained. Then, the weighting function characteristics of the initial channel group are studied. The channels located at the bottom and top of the peaks in the CO absorption spectrum, suggesting abundant gas retrieval information of different atmospheric layer, are selected as the final channel selection results. The channel selection method is applied for the winter and summer air masses in Alxa desert area, Beijing-Tianjin area, Yangtze River Delta, and Pearl River Delta. By comparing with the Optimal Sensitivity Profile method (OSP), the channels selected by the proposed method can cover a wider spectral range and have more CO absorption characteristics. Additionally, the application of the proposed method can improve the retrieval accuracy of CO profiles in all the regions and seasons studied in this paper. The best improvement effect was observed in the Alxa desert area in winter, whose root mean square error (RMSE) was reduced from 3.23×10-8 g/g to 3.07×10-8 g/g, with an average increase in accuracy of 10.56%.
keywords:Channel  selection, CO  profile retrieval, ultra-spectral  thermal infrared  data, sensitivity, weighting  function characteristics
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