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首页> 外文会议>Remote Sensing of Clouds and the Atmosphere XII; Proceedings of SPIE-The International Society for Optical Engineering; vol.6745 >Retrieval of atmospheric temperature and water vapour content from thermal infrared hyperspectral data in a purpose of atmospheric compensation
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Retrieval of atmospheric temperature and water vapour content from thermal infrared hyperspectral data in a purpose of atmospheric compensation

机译：从热红外高光谱数据中检索大气温度和水蒸气含量，以进行大气补偿

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摘要

Infrared hyperspectral imagery gives new opportunities for night observations for military, or security purposes, and for geological studies as rocks have specific infrared absorption bands. Generally, an optimized utilization of spectral information requires to retrieve spectral emissivity, which involves atmospheric compensation and surface temperature and emissivity separation (TES). This paper presents a new method dedicated to a future airborne hyperspectral sensor that will operate in the 3-5.5 and 8-12 μm spectral ranges, at 2.2 km height. It combines neural networks in order to characterize the required parameters for atmospheric compensation and a spectral smoothness approach for TES. The network training is performed with radiance spectra simulated with MODTRAN4, and using ASTER emissivities, and the TIGR atmospheric database. A sensitivity study based on experimental design is carried out in order to compare impacts of atmospheric and surface parameters on radiance at several wavelengths. Atmospheric compensation and TES methods are then presented and their accuracy is assessed. Sensitivity of the retrievals to instrumental characteristics such as signal to noise ratio and radiometric calibration, is also studied.
机译：由于岩石具有特定的红外吸收带，因此红外高光谱图像为军事或安全目的进行夜间观察提供了新的机会，并为地质研究提供了新的机会。通常，光谱信息的优化利用需要检索光谱发射率，这涉及大气补偿以及表面温度和发射率分离（TES）。本文介绍了一种专门针对未来机载高光谱传感器的新方法，该传感器将在3-5.5和8-12μm的光谱范围内，2.2 km的高度上运行。它结合了神经网络以表征大气补偿所需的参数和TES的光谱平滑度方法。网络训练是使用MODTRAN4模拟的辐射光谱，ASTER发射率和TIGR大气数据库进行的。为了比较大气和表面参数对几种波长辐射的影响，进行了基于实验设计的敏感性研究。然后介绍了大气补偿和TES方法，并评估了其准确性。还研究了取回对仪器特性（如信噪比和辐射校准）的敏感性。

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