A Multi-wavelength Analysis of Active Regions and Sunspots by Comparison of Automatic Detection Algorithms
A Multi-wavelength Analysis of Active Regions and Sunspots by Comparison of Automatic Detection Algorithms
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DOI：
10.1007/s11207-011-9859-6
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发表时间：
2011-09
期刊：
影响因子：
2.8
通讯作者：
C. Verbeeck;P. Higgins;T. Colak;F. Watson;V. Delouille;B. Mampaey;R. Qahwaji
中科院分区：
文献类型：
--
作者：
C. Verbeeck;P. Higgins;T. Colak;F. Watson;V. Delouille;B. Mampaey;R. Qahwaji
自从太阳动力学天文台（SDO）开始每天记录101 TB的数据以来，自动提取特征和事件以供进一步分析的需求不断增加。在这里，我们比较了四种太阳特征检测算法的整体检测性能、提取属性之间的相关性以及特征跟踪的可用性：太阳监测活动区跟踪器（SMART）检测视线磁图中的活动区;自动太阳活动预测代码（ASAP）检测白光连续图像中的太阳黑子和气孔;太阳黑子跟踪和识别算法（STARA）检测白光连续图像中的太阳黑子;空间可能性聚类算法（SPoCA）自动将太阳EUV图像分割为活动区域（AR）、冕洞（CH）和安静太阳（QS）。本文分析了2003年5月12日至6月23日太阳和日光层天文台（SOHO）/迈克尔逊多普勒成像仪（MDI）和SOHO/极紫外成像望远镜（EIT）的一个月观测资料。每个算法的整体检测性能是基准对美国国家海洋和大气管理局（NOAA）和太阳影响数据分析中心（SIDC）目录使用各种功能属性，如总太阳黑子面积，这表明良好的协议，和检测到的功能，这表明协议差的数量。主成分分析表明，光球属性，这是高度相关的第一个组成部分，并占数据集的变异性的52.86%，和日冕属性，这是适度相关的第一和第二主成分之间的明显区别。最后，NOAA 10377和10365的案例研究进行，以确定算法的稳定性跟踪个别功能的演变。我们发现，磁通量和太阳黑子总面积是活跃区出现的最佳指标。此外，对于NOAA 10365，它表明，发作的耀斑发生在这两个时期的磁通量出现和复杂性的发展。
Since theSolar Dynamics Observatory(SDO) began recording ≈ 1 TB of data per day, there has been an increased need to automatically extract features and events for further analysis. Here we compare the overall detection performance, correlations between extracted properties, and usability for feature tracking of four solar feature-detection algorithms: the Solar Monitor Active Region Tracker (SMART) detects active regions in line-of-sight magnetograms; the Automated Solar Activity Prediction code (ASAP) detects sunspots and pores in white-light continuum images; the Sunspot Tracking And Recognition Algorithm (STARA) detects sunspots in white-light continuum images; the Spatial Possibilistic Clustering Algorithm (SPoCA) automatically segments solar EUV images into active regions (AR), coronal holes (CH), and quiet Sun (QS). One month of data from theSolar and Heliospheric Observatory(SOHO)/Michelson Doppler Imager(MDI) and SOHO/Extreme Ultraviolet Imaging Telescope(EIT) instruments during 12 May – 23 June 2003 is analysed. The overall detection performance of each algorithm is benchmarked against National Oceanic and Atmospheric Administration (NOAA) and Solar Influences Data Analysis Center (SIDC) catalogues using various feature properties such as total sunspot area, which shows good agreement, and the number of features detected, which shows poor agreement. Principal Component Analysis indicates a clear distinction between photospheric properties, which are highly correlated to the first component and account for 52.86% of variability in the data set, and coronal properties, which are moderately correlated to both the first and second principal components. Finally, case studies of NOAA 10377 and 10365 are conducted to determine algorithm stability for tracking the evolution of individual features. We find that magnetic flux and total sunspot area are the best indicators of active-region emergence. Additionally, for NOAA 10365, it is shown that the onset of flaring occurs during both periods of magnetic-flux emergence and complexity development.