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Open AccessArticle

Automatic Detection of Lightning Whistlers Observed by the Plasma Wave Experiment Onboard the Arase Satellite Using the OpenCV Library

1
Graduate School of Natural Science and Technology, Kanazawa University, Kakuma-machi, Kanazawa 920-1192, Japan
2
School of Electrical Engineering, Telkom University, Jl. Telekomunikasi No.1 Dayeuhkolot, Kab. Bandung 40257, Indonesia
3
Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (JAXA), Sagamihara, Kanagawa 252-5210, Japan
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(15), 1785; https://doi.org/10.3390/rs11151785
Received: 6 June 2019 / Revised: 23 July 2019 / Accepted: 27 July 2019 / Published: 30 July 2019
The automatic detection of shapes or patterns represented by signals captured from spacecraft data is essential to revealing interesting phenomena. A signal processing approach is generally used to extract useful information from observation data. In this paper, we propose an image analysis approach to process image datasets produced via plasma wave observations by the Arase satellite. The dataset consists of 31,380 PNG files generated from the dynamic power spectra of magnetic wave field data gathered from a one-year observation period from March 2017 to March 2018. We implemented an automatic detection system using image analysis to classify the various types of lightning whistlers according to the Arase whistler map. We successfully detected a large number of whistler traces induced by lightning strikes and recorded their corresponding times and frequencies. The various shapes of the lightning whistlers indicate different very-low-frequency propagations and provide important clues concerning the geospace electron density profile. View Full-Text
Keywords: whistler mode waves; automatic detection; lightning whistler; satellite; plasmasphere; image analysis whistler mode waves; automatic detection; lightning whistler; satellite; plasmasphere; image analysis
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MDPI and ACS Style

Ali Ahmad, U.; Kasahara, Y.; Matsuda, S.; Ozaki, M.; Goto, Y. Automatic Detection of Lightning Whistlers Observed by the Plasma Wave Experiment Onboard the Arase Satellite Using the OpenCV Library. Remote Sens. 2019, 11, 1785.

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