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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Evaluation of Temperature and Emissivity Retrieval using Spectral Smoothness Method for Low-Emissivity Materials
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Evaluation of Temperature and Emissivity Retrieval using Spectral Smoothness Method for Low-Emissivity Materials

机译：用光谱平滑度法评估低发射率材料的温度和发射率

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摘要

Land surface temperature and emissivity separation (TES) is a key problem in thermal infrared (TIR) remote sensing. Along with the development of civil applications, increasing numbers of man-made low-emissivity materials can be found around our living environment. In addition, the characteristics and variation in properties of those materials should also be concerned. However, there are still few TES methods for low-emissivity materials reported in the literature. This paper addresses the performance of the automatic retrieval of temperature and emissivity using spectral smoothness (ARTEMISS) method proposed by Borel (2008) for the retrieval of temperature and emissivity from hyperspectral TIR data for low-emissivity materials. The results show that those modeling errors are less than 0.11 K for temperature and 0.3% for emissivity as shown in the ARTEMISS algorithm if atmospheric parameters and the mean emissivity of material spectra are known. A sensitivity analysis has been performed, and the results show that the retrieval accuracy will be degraded with the increase of instrument noises, the errors of the atmospheric parameters, and the coarser spectral resolution. ARTEMISS can give a reasonable estimation of the temperature and emissivity for high- and low-emissivity materials; however, the performance of the algorithm is more seriously influenced by the atmospheric compensation than by the instrument noises. Our results show that the errors of temperature and emissivity become approximately three times than that when the instrument spectral properties are 1 cm-1 of sampling interval and 2 cm-1 of FWHM, and 4 cm-1 of sampling interval and 8 cm-1 of FWHM, respectively.
机译：地表温度和发射率分离（TES）是热红外（TIR）遥感中的关键问题。随着民用应用的发展，在我们的生活环境中发现了越来越多的人造低辐射材料。此外，还应考虑这些材料的特性和性能变化。但是，文献中报道的低发射率材料的TES方法仍然很少。本文讨论了由Borel（2008）提出的利用光谱平滑度（ARTEMISS）方法自动检索温度和发射率的性能，该方法用于从低发射率材料的高光谱TIR数据中检索温度和发射率。结果表明，如果已知大气参数和材料光谱的平均发射率，则这些建模误差对于温度小于0.11 K，对于发射率小于0.3％，如ARTEMISS算法所示。进行了灵敏度分析，结果表明，随着仪器噪声，大气参数误差和光谱分辨率的提高，检索精度将降低。 ARTEMISS可以合理估计高和低发射率材料的温度和发射率；但是，算法的性能受大气补偿的影响比受仪器噪声的影响更大。我们的结果表明，温度和发射率的误差约为仪器光谱特性为采样间隔1 cm-1和FWHM 2 cm-1以及采样间隔4 cm-1和8 cm-1时的三倍。分别为FWHM。

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    Yonggang Qian; Ning Wang; Lingling Ma; Chen Mengshuo; Hua Wu; Li Liu; Qijin Han; Caixia Gao; Jia Yuanyuan; Lingli Tang; Chuanrong Li;

  • 作者单位

    Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing, China;

    Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing, China;

    Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing, China;

    Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing, China;

    State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China;

    Application Research Department, China Center for Resources Satellite Data and Application, Beijing, China;

    Application Research Department, China Center for Resources Satellite Data and Application, Beijing, China;

    Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing, China;

    Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing, China;

    Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing, China;

    Key Laboratory of Quantitative Remote Sensing Information Technology, Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing, China;

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  • 关键词

    Atmospheric modeling; Atmospheric measurements; Temperature distribution; Temperature measurement; Temperature sensors; Hyperspectral imaging;

    机译：大气建模;大气测量;温度分布;温度测量;温度传感器;高光谱成像;

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