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• W2897089074 abstract "Abstract With new space missions, such as Solar Dynamics Observatory (SDO), solar images are being produced in unprecedented volumes. To derive, as much as possible, information on evolution of solar activity from those huge datasets, the scientific community needs a new generation of software tools for automatic and efficient data processing. In the last decade, several research teams have been developing tools for obtaining more precise estimations of the solar rotation profile, but more are needed to improve knowledge about solar activity. We applied here a segmentation algorithm called Gradient Path Labelling (GPL), used originally to identify drusens in medical retinal images, to detect and track the coronal bright points (CBPs) using images from the AIA instrument onboard the SDO satellite. The CBPs have a tendency to change shape and size along time, to disappear and reappear at a corresponding heliographic position, therefore, decision trees were also included in the tracking solution. Since our CBP detection algorithm uses an active region mask to filter out the CBPs, whose centroid is inside the active regions, the number of identifications clearly depends on the level of solar activity. Our approach uses the commonly applied fitting relation to the latitudinal dependence of the rotational velocity, which resulted in calculation of the optimum fit parameters as well as the Gegenbauer orthogonal polynomials. Comparison of these parameters with the results presented in recent papers on this topic shows that our rotational velocity profile indicates slightly lower rotational velocities than the profiles obtained with other approaches. We also calculate the meridional motion of the CBPs, but comparison with other authors results, clearly show that a 3-day time interval is too short to estimate the latitudinal dependence of the CBP meridional motion. Distributions of the rotational velocity and meridional motion velocity uncertainties show that 85% of uncertainty values are lower than 1 degree/day. The evaluation of our test results shows that the applied algorithm is a promising tool that can help to refine the solar rotational profile." @default.
• W2897089074 created "2018-10-26" @default.
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• W2897089074 date "2018-10-01" @default.
• W2897089074 modified "2023-10-16" @default.
• W2897089074 title "Gradient Path Labelling method and tracking method for calculation of solar differential rotation using coronal bright points" @default.
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• W2897089074 doi "https://doi.org/10.1016/j.ascom.2018.09.008" @default.
• W2897089074 hasPublicationYear "2018" @default.
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