Extracting High Temperature Event radiance from satellite images and correcting for saturation using Independent Component Analysis
Extracting High Temperature Event radiance from satellite images and correcting for saturation using Independent Component Analysis
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DOI：
10.1016/j.rse.2014.10.023
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发表时间：
2015-03-01
影响因子：
13.5
通讯作者：
Oppenheimer, Clive
中科院分区：
文献类型：
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作者：
Barnie, Talfan;Oppenheimer, Clive
提出了一种利用独立分量分析（ICA）从地球静止成像仪记录的高温事件（HTEs）中提取辐射的新方法。我们使用ICA将仪器收集的图像立方体分解为独立的非高斯时间序列及其空间分布的图像的外部乘积的总和，然后仅使用看起来是hte的源重新组装图像立方体。空间积分得到HTE总辐射发射的时间序列。在本研究中，我们在一些模拟的高温高温事件上测试了该技术，然后将其应用于SEVIRI仪器观测到的一些火山高温高温事件。我们发现该技术在小的局部喷发上表现良好，可以用来校正饱和度。该技术的优点是，除了对场景中影响亮度的过程的性质的一些基本假设之外，不需要对被成像区域的先验知识，即(i) HTE源在统计上独立于其他过程，（ii）传感器上记录的亮度是HTE信号和其他过程的线性混合，以及（iii） HTE源可以可靠地识别用于重建过程。这导致只有五个自由参数：图像立方体的维度、数据维度的估计和区分HTE和非HTE源的阈值。虽然我们在这里关注的是火山高温排放，但原则上，该方法可以扩展到其他类型的高温排放的研究，例如与生物质燃烧有关的高温排放。(C) 2014年作者。Elsevier Inc.出版。
We present a novel method for extracting the radiance from High Temperature Events (HTEs) recorded by geo-stationary imagers using Independent Component Analysis (ICA). We use ICA to decompose the image cube collected by the instrument into a sum of the outer products of independent, maximally non-Gaussian time series and images of their spatial distribution, and then reassemble the image cube using only sources that appear to be HTEs. Integrating spatially gives the time series of total HTE radiance emission. In this study we test the technique on a number of simulated HTE events, and then apply it to a number of volcanic HTEs observed by the SEVIRI instrument. We find that the technique performs well on small localised eruptions and can be used to correct for saturation. The technique offers the advantage of obviating the need for a priori knowledge of the area being imaged, beyond some basic assumptions about the nature of the processes affecting radiance in the scene, namely that (i) HTE sources are statistically independent from other processes, (ii) the radiance registered at the sensor is a linear mixture of the HTE signal and those from other processes, and (iii) HTE sources can be reliably identified for the reconstruction process. This results in only five free parameters the dimensions of the image cube, an estimate of the data dimensionality and a threshold for distinguishing between HTE and nonHTE sources. While we have focused here on volcanic HTEs, the methodology can, in principle, be extended to studies of other kinds of HTEs such as those associated with biomass burning. (C) 2014 The Authors. Published by Elsevier Inc.