Automated Sunspot Detection and Classification Using SOHO/MDI Imagery

Abstract

This research modifies and expands previous work by Spahr in 2014 to automatically identify and classify sunspot groups in satellite images. Data from the Solar and Heliospheric Observatory (SOHO) are analyzed to produce a database of sunspot information that is not biased by individual solar observers. Results of the algorithm on SOHO/MDI data correlate well with NOAA's reported data for region properties with R2 values greater than 0.75, but with a ratio of less than one. In particular, the results of analyzing SOHO data report less than 25% of the spots reported by NOAA. By considering a test case comparison with an SDO observation, resolution is likely the main factor in detection discrepancies. 15.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2015
Accession Number
ADA621617

Entities

People

  • Samantha R. Howard

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Advanced Electronics
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Acquisition
  • Air Force
  • Algorithms
  • Artificial Satellites
  • Change Detection
  • Charge Coupled Devices
  • Cosmic Rays
  • Databases
  • Detection
  • Image Processing
  • Measurement
  • Observation
  • Observatories
  • Observers
  • Solar Activity
  • Solar Flares
  • Visible Spectra

Fields of Study

  • Environmental science

Readers

  • Computational Modeling and Simulation
  • Sensor Fusion and Tracking Systems.
  • Solar Physics

Technology Areas

  • Space
  • Space - Space Objects