Dataset of Solar Prominences from 2011 to 2022

Solar prominences are magnetic structures suspended in the corona, characterized by relatively low temperatures (typically below 10000K) and higher electron densities(10⁹～10¹¹ cm^–3). Research indicates a clear correlation between prominences and solar eruptive activities, such as solar flares and coronal mass ejections that may trigger hazardous space weather. Studying the spatiotemporal distribution of solar prominences can aid in forecasting space weather efforts and help mitigate potential catastrophic impacts. This dataset is based on the 30.4 nm wavelength images captured by the Atmospheric Imaging Assembly (AIA) instrument aboard the Solar Dynamics Observatory (SDO) satellite, with a temporal resolution of 10 minutes. By employing background reconstruction to enhance the contrast of off-limb images, the automated algorithms, such as the skeleton extraction and the region-growing techniques, were used to identify prominence regions in the reconstructed images and extract relevant parameters. For those evolving in the same region during continuous frames, Misidentification caused by duplicate naming is avoided by K-Nearest Neighbor (KNN) classification . Before tracking a procedure called non-prominence feature removal is used to discriminate real prominences from non-prominence features: Through Linear Discriminant Analysis (LDA), the eigenvalue of any target region can be calculated, and compare it with the derived distribution which is fitted with Gaussian distribution functions, to determine the likeliness of a real prominence, by which SLIPCAT can exclude active regions without involving other observation methods. Persisting prominences were tracked and stored in data files. At last, the processed images and prominence data files are organized in a year-month-day three-level directory structure. The dataset encompasses a total of 101741 prominence files, covering the period from 00:00 UT on 1 January 2011 to 23:50 UT on 31 December 2022. Rigorous validation was conducted in accordance with relevant protocols and classification standards to ensure high reliability. This dataset provides scientific support for research on the spatiotemporal distribution of solar prominences over their activity cycles and for the prediction of hazardous space weather events.