Cloud identification and classification from high spectral resolution data in the far infrared and mid-infrared
Cloud identification and classification from high spectral resolution data in the far infrared and mid-infrared
复制标题
远红外和中红外高光谱分辨率数据的云识别和分类
DOI：
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复制
发表时间：
2019
影响因子：
3.8
通讯作者：
Iacopo Sbrolli
中科院分区：
文献类型：
--
作者：
T. Maestri;William Cossich;Iacopo Sbrolli
抽象的。提出了一种新的云识别与分类算法CIC。CIC是一种基于主成分分析的机器学习算法，能够使用相似性指数的单变量分布来执行云检测和场景分类，该相似性指数定义了分析的光谱与每个训练数据集的元素之间的接近程度。CIC在光谱的远红外和中红外部分的高光谱分辨率辐射的广泛合成数据集上进行测试，模拟来自Fast Track 9使命论坛（远红外向外辐射理解和监测）的测量，竞争欧空局地球探测器计划，该计划目前（2018年和2019年）正在进行工业和科学阶段A研究。模拟的光谱代表了从热带到极地的许多不同的气候区域。将该算法应用于合成数据集为清晰或云识别提供了高分，特别是在执行优化过程时。其中一个主要的结果是指出了高信息含量的光谱辐射在远红外区域的电磁频谱，以确定多云的场景，特别是薄卷云。特别是，它示出，命中分数清晰和多云光谱增加约70%至90%时，远红外通道占在热带地区的合成数据集的分类。
Abstract. A new cloud identification and classification algorithm named CIC is presented. CIC is a machine learning algorithm, based on principal component analysis, able to perform a cloud detection and scene classification using a univariate distribution of a similarity index that defines the level of closeness between the analysed spectra and the elements of each training dataset. CIC is tested on a widespread synthetic dataset of high spectral resolution radiances in the far- and mid-infrared part of the spectrum, simulating measurements from the Fast Track 9 mission FORUM (Far-Infrared Outgoing Radiation Understanding and Monitoring), competing for the ESA Earth Explorer programme, which is currently (2018 and 2019) undergoing industrial and scientific Phase A studies. Simulated spectra are representatives of many diverse climatic areas, ranging from the tropical to polar regions. Application of the algorithm to the synthetic dataset provides high scores for clear or cloud identification, especially when optimisation processes are performed. One of the main results consists of pointing out the high information content of spectral radiance in the far-infrared region of the electromagnetic spectrum to identify cloudy scenes, specifically thin cirrus clouds. In particular, it is shown that hit scores for clear and cloudy spectra increase from about 70 % to 90 % when far-infrared channels are accounted for in the classification of the synthetic dataset for tropical regions.
DOI：
10.1016/j.jqsrt.2013.07.002
发表时间：
2013-11-01
影响因子：
2.3
作者：
Rothman, L. S.;Gordon, I. E.;Wagner, G.
通讯作者：
Wagner, G.