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Different methods for temperature and spectral emissivity retrieval over active fires from IR hyperspectral remotely sensed data

机译:来自IR Hyperspectral栅极偏远数据的热量和光谱发射率的不同方法。

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We have developed a theoretical model which allows us to retrieve the temperature of burning areas employing the thermal infrared spectral-radiance data gathered by the used sensor. The algorithm performs the temperature-emissivity separation by coupling together radiance data from a pair of neighbouring similar image pixels, which are assumed to have the same emissivity spectrum and independent temperatures. The characteristic uncertainty in the basic thermal infrared equations is thus resolved using a double number of spectral measurements (radiance samples) for the temperature estimation. Results produced by this model have been compared with fire-front temperatures assessed utilising spectral data collected at short-wave infrared wavelengths between 1.99 μm and 2.48 μm. Moreover, we have also applied the GBE-method for retrieving the pixel temperature and spectral emissivity utilising thermal infrared spectral data. In order to test the three considered methods, we have utilised a rare example of airborne hyperspectral image acquired over a natural active fire. This image was collected by the MIVIS operated on board of a Casa 212 airplane over the Alps (Italy). The paper shows the image acquired by the MIVIS sensor, the related processing and is completed with a theoretical discussion of the involved topics.
机译:我们开发了一种理论模型,使我们能够检索采用由使用的传感器收集的热红外光谱辐射数据的燃烧区域的温度。该算法通过从一对相邻的类似图像像素耦合到相邻的类似图像像素一起进行温度发射率分离,这被假设具有相同的发射频率和独立温度。因此,使用用于温度估计的双数量的光谱测量(RADICES样本)来解决基本热红外方程中的特征不确定性。通过利用在1.99μm和2.48μm的短波红外波长下收集的光谱数据进行评估的射击数据,将该模型产生的结果进行了比较。此外,我们还应用了用于利用热红外光谱数据检索像素温度和光谱发射率的GBE-方法。为了测试三种考虑的方法,我们利用了在天然活性的火灾中获得的空中高光谱图像的罕见例子。在阿尔卑斯山(意大利)的Casa 212飞机上运行的Mivis收集了该图像。本文显示了由Mivis传感器获取的图像,相关处理并完成了对涉及主题的理论讨论。

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