Date of Award
3-24-2016
Document Type
Thesis
Degree Name
Master of Science in Applied Physics
Department
Department of Engineering Physics
First Advisor
Robert D. Loper, PhD.
Abstract
Verification of an automated sunspot detection and classification algorithm is conducted utilizing two years of solar imagery from NASA's Solar Dynamics Observatory (SDO) satellite. Automated McIntosh classifications are compared against sunspot reports from the National Oceanic and Atmospheric Administration’s (NOAA) Space Weather Prediction Center (SWPC) using a three-tiered comparison metric. Statistical confidence is demonstrated for algorithm performance and consistency when compared against the SWPC data set, suggesting future applications of the algorithm will perform similarly. A sunspot tracking algorithm is added to the existing code and demonstrates reliable feature tracking for time periods out to four days between consecutive images. Finally, an empirical Mount Wilson Magnetic Classification algorithm is generated with early testing exhibiting a direct match of 79.78% with SWPC magnetic classifications.
AFIT Designator
AFIT-ENP-MS-16-M-083
DTIC Accession Number
AD1053930
Recommended Citation
Townsend, MacLane A., "Automated Sunspot Classification and Tracking Using SDO/HMI Imagery" (2016). Theses and Dissertations. 349.
https://scholar.afit.edu/etd/349