Supnithi, Pornchai

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Supnithi, Pornchai
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Supnithi, P.
Supnithi, Pomchai
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pornchai.su@kmitl.ac.th

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    Total electron content observations by dense regional and worldwide international networks of GNSS
    (2018-06-01)
    Tsugawa, Takuya
    ;
    Nishioka, Michi
    ;
    Ishii, Mamoru
    ;
    Hozumi, Kornyanat
    ;
    Saito, Susumu
    Two-dimensional ionospheric total electron content (TEC) maps have been derived from ground-based Global Navigation Satellite System (GNSS) receiver networks and applied to studies of various ionospheric disturbances since the mid-1990s. For the purpose of monitoring and researching ionospheric conditions and ionospheric space weather phenomena, we have developed TEC maps of areas over Japan using the dense GNSS network, GNSS Earth Observation NETwork (GEONET), which consists of about 1300 stations and is operated by the Geospatial Information Authority of Japan (GSI). Currently, we are providing high-resolution, two-dimensional maps of absolute TEC, detrended TEC, rate of TEC change index (ROTI), and loss-of-lock on GPS signal over Japan on a real-time basis. Such high-resolution TEC maps using dense GNSS receiver networks are one of the most effective ways to observe, on a scale of several 100 km to 1000 km, ionospheric variations caused by traveling ionospheric disturbances and/or equatorial plasma bubbles, which can degrade single-frequency and differential GNSS positioning/navigation. We have collected all the available GNSS receiver data in the world to expand the TEC observation area. Currently, however, dense GNSS receiver networks are available in only limited areas, such as Japan, North America, and Europe. To expand the two-dimensional TEC observation with high resolution, we have conducted the Dense Regional and Worldwide International GNSS TEC observation (DRAWING-TEC) project, which is engaged in three activities: (1) standardizing GNSS-TEC data, (2) developing a new high-resolution TEC mapping technique, and (3) sharing the standardized TEC data or the information of GNSS receiver network. We have developed a new standardized TEC format, GNSS-TEC EXchange (GTEX), which is included in the Formatted Tables of ITU-R SG 3 Data-banks related to Recommendation ITU-R P.311. Sharing the GTEX TEC data would be easier than sharing the GPS/GNSS data among those in the international ionospheric researcher community. The DRAWING-TEC project would promote studies of medium-scale ionospheric variations and their effect on GNSS.
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    Classification of Equatorial Ionospheric Irregularities Using Unsupervised Machine Learning Based on Spatiotemporal ROTI Keograms
    (2025-01-01)
    Mutasov, Gleb
    ;
    Supnithi, Pornchai
    ;
    Budtho, Jirapoom
    ;
    Tongkasem, Napat
    ;
    Nishioka, Michi
    Equatorial ionospheric irregularities, particularly those associated with equatorial plasma bubbles (EPB), can significantly disrupt satellite navigation and communication systems. As the demand for reliable Global Navigation Satellite System (GNSS) and communication services grows, the prediction of ionospheric irregularities becomes critical. A key step in the prediction process is to identify distinct spatiotemporal patterns of irregularities, including day-to-day, longitudinal, and seasonal variations. However, with large datasets, manually classification or identification of these irregularities is a complex and challenging task. In this work, we propose unsupervised machine learning techniques to recognize and group irregularity patterns in large, unlabeled Rate of Total Electron Content (TEC) Index (ROTI) keograms. Specifically, two machine learning models: Gaussian Mixture Model and k-means clustering are employed. The ROTI keograms are constructed using GNSS data from two low-latitude receiver stations in Thailand. To reduce redundancy in the keogram images, three feature extraction techniques are applied before the clustering process. A comparative analysis is performed to determine the optimal number of clusters using these models. Based on the results, the optimal combination of feature extraction and clustering technique is determined for the proposed clustering model. The resulting k-means model with contour extractor classifies five distinct patterns of ionospheric irregularity patterns, providing valuable insights for enhancing EPB prediction models and deepening our understanding of ionospheric dynamics. Furthermore, these five irregularity patterns are analyzed in relation to space weather parameters such as the solar radio flux index (F10.7), and the geomagnetic index (Kp). The findings contribute to the development of robust prediction models, improving the reliability of satellite-based communication and navigation systems.
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    Analysis of ionospheric and geomagnetic fields changes in Thailand during the May 2024 geomagnetic storm
    (2025-12-15)
    Myint, Lin M.M.
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    Perwitasari, Septi
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    Nishioka, Michi
    ;
    Saito, Susumu
    ;
    Kaewthongrach, Rungnapa
    The extreme geomagnetic storm of May 2024, the most severe in two decades of space weather history up to date, had widespread effects on the ionosphere, from the polar regions to the magnetic equator. This study examines the responses of the equatorial ionosphere and geomagnetic field over Thailand during this geomagnetic storm, utilizing data from GNSS receivers, magnetometers, and ionosondes near the magnetic equator and low-latitude regions of Thailand. We analyze the direct and indirect impacts of interplanetary magnetic field (IMF) and interplanetary electric field (IEF) variations, driven by solar storms, on local equatorial magnetic fields and ionospheric parameters. Our finding reveals that storm-driven electric fields, particularly prompt penetration electric fields (PPEF) and disturbance dynamo electric fields (DDEF), strongly influenced equatorial electric field (EEF), causing notable fluctuations in total electron content (TEC), critical frequency of F2 (foF2), and virtual height of F layer (h’F). The Pearson correlation analysis highlights the rapid coupling between interplanetary magnetic field (IMF) and local equatorial magnetic fields during geomagnetic storms. These observations enhance our understanding of geomagnetic storm impacts in equatorial regions, which is crucial for improving space weather forecasting and mitigation strategies, especially for GNSS-dependent systems and radio communications.
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    Local mitigation of higher-order ionospheric effects in DFMC SBAS and system performance evaluation
    (2024-04-01)
    Sophan, Somkit
    ;
    Supnithi, Pornchai
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    Myint, Lin M.M.
    ;
    Saito, Susumu
    ;
    Hozumi, Kornyanat
    Dual-frequency multi-constellation (DFMC) satellite-based augmentation system (SBAS) is a new SBAS standard for aeronautical navigation systems. It supports aircraft navigation from the enroute to approach phases via the L1 and L5 frequencies (1575.42 and 1176.45 MHz). Although the ionosphere-free (IF) combination in the DFMC SBAS operation removes the first-order ionospheric delays in the pseudorange measurement, remaining terms including the satellite-clock offset errors and higher-order ionospheric (HOI) delays are still unaccounted for. The DFMC SBAS accuracy and integrity can be affected by the HOI effects, especially during severe ionospheric disturbances. In this work, we present the local DFMC SBAS corrections with and without the mitigation of HOI delays. We first estimate the HOI delay terms using the received pseudorange followed by separate satellite and receiver bias estimations based on the minimum sum-variance technique. The integrity terms can then be obtained. The performances of DFMC SBAS using the global navigation satellite system (GNSS) data including GPS, Galileo, and QZSS are evaluated using obtained GNSS data at stations in Thailand on the ionospheric quiet and disturbed days. The results show that with the HOI mitigation, the vertical positioning errors (VPE) on the quiet and disturbed days can be improved by 12% and 9%, whereas the vertical protection levels (VPL) are improved by 16% and 21%, respectively. In addition, we perform a preliminary assessment of DFMC SBAS based on the International Civil Aviation Organization (ICAO) requirements of two categories: Localizer Performance with Vertical guidance (LPV-200) and Category I precision approach (CAT-I) showing promising results.
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    Spatio-temporal characteristics of ionospheric irregularities in low latitude regions during the peak of solar cycle 25
    (2025-07-01)
    Tongkasem, Napat
    ;
    Supnithi, Pornchai
    ;
    Thammavongsy, Phimmasone
    ;
    Nishioka, Michi
    ;
    Perwitasari, Septi
    Equatorial plasma bubbles (EPBs) are a primary source of ionospheric irregularities (IIR) in low-latitude regions. The severity of EPBs depends on the intensity, penetration, and disturbance of electric fields generated in the ionosphere. In this work, we analyze the IIR associated with geomagnetic activity in the low-latitude region (0°N–25°N, 90°E–110°E) from 2022 to 2024. The total electron content (TEC) and the rate of TEC index (ROTI) are used to investigate the spatiotemporal characteristics of these IIRs, influenced by both local EPBs and global geomagnetic storms. During low-to-moderate geomagnetic activity, electric field penetration and disturbances have a low impact on EPB development. The high solar activity intensifies the electric field, leading to intense EPB occurrences that can affect the entire region for several hours. From January 2022 to October 2024, these intense EPB events accounted for 35% of all EPB occurrences. During strong geomagnetic storms, the prompt penetration of electric fields (PPEF), and disturbance dynamo electric field (DDEF) caused the depression and fluctuations of TECs.
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    Simultaneous equatorial plasma bubble observation using amplitude scintillations from GNSS and LEO satellites in low-latitude region
    (2023-12-01)
    Seechai, Khanitin
    ;
    Myint, Lin Min Min
    ;
    Hozumi, Kornyanat
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    Nishioka, Michi
    ;
    Saito, Susumu
    This study estimates the scale sizes of the plasma density irregularities and the longitudinal width associated with equatorial plasma bubbles (EPBs) in equatorial and low-latitude regions. By analyzing amplitude scintillation S<inf>4</inf> indices and total electron content (TEC) measured from low earth orbit (LEO) satellite’s beacon signals with 400 MHz and Global Navigation Satellite System (GNSS) L1/E1 signals with 1575.42 MHz, recorded by receivers at the KMITL station in Bangkok, Thailand (geographic; 13.73° N, 100.77°E, magnetic: 7.26°N), we investigate the characteristics of these irregularities. We collected data of 154 LEO satellite pass events during nighttime on 21 disturbed days in four equinoctial months in 2021. Based on the presence or absence of the scintillation effects on GNSS and LEO beacon signals, the events are categorized into four classes to estimate the scale size of the plasma density irregularities. The analysis suggests that events with both GNSS and LEO scintillations, as well as events with GNSS scintillation alone, occur predominantly before midnight assuming the presence of the small-scale size of the irregularities within EPB. However, events with only LEO scintillation occur throughout the whole night and some events are observed before the events with both GNSS and LEO scintillations. Post-sunset LEO scintillation alone may be attributed to the onset of EPBs developing at low altitude, while post-midnight LEO scintillation events near the magnetic equator, observed during periods of low GNSS Rate of TEC Index (ROTI) values, are associated with bottom-side ionospheric irregularities but are not linked with EPB. The findings are consistent with previous researches on the generation and decay of electron density irregularities within plasma bubbles. However, this study provides new insights by using specific data sets and analysis techniques, offering a more comprehensive understanding of the association of LEO scintillations with bottom-side ionospheric irregularities near the magnetic equator, not observed in the ROTI map. Graphical Abstract: [Figure not available: see fulltext.]
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    Sporadic E critical frequency detection using three EIA region ionosonde stations over Southeast Asia
    (2025-03-01)
    Wichaipanich, Noraset
    ;
    Nishioka, Michi
    ;
    Min Myint, Lin Min
    ;
    Supnithi, Pornchai
    This paper presents the occurrence of the sporadic E layer critical frequency (foEs) measured from three ionosonde stations in the Southeast Asia equatorial ionization anomaly (EIA) regions. These three ionosonde stations include two in Thailand: Chiang Mai (18.76°N, 98.93°E, Dip 12.7°) and Chumphon (10.72°N, 99.37°E, Dip 3.0°), and one in Indonesia: Kototabang (0.2°S, 100.32°E, Dip −10.1°). The daily hourly foEs values observed during 2010 and 2015 were statistically analyzed for foEs occurrence during low and high solar activity periods. Additionally, the number of foEs occurrences was analyzed in terms of the percentage of occurrence (%foEs). The results show that the occurrences of foEs from all three stations were similar, with the monthly hourly occurrence of foEs peaking in the June solstice season (May, June, July, August). Meanwhile, foEs appeared relatively low during the September equinox (September, October) and the December solstice (November, December, January, February) seasons. Furthermore, the frequency of foEs occurrence peaks around 16–20 LT, except in 2015 at Chiang Mai and Chumphon, where peaks were observed at 10 LT and 15 LT, respectively. Additionally, comparing the three stations reveals that in 2010, the maximum number of foEs occurrences was at Chiang Mai (≈21 %), followed by Kototabang (≈19 %) and Chumphon (≈16 %). In 2015, the highest number was observed at Kototabang (≈17 %), followed by Chumphon (≈14 %) and Chiang Mai (≈8%). Furthermore, the maximum frequency of foEs was highest at Chiang Mai (20–25 MHz), followed by Chumphon (15–20 MHz) and Kototabang (10–15 MHz). Additionally, foEs occurrences during low solar activity (2010) were higher than those during high solar activity (2015). It was assumed that the occurrence of foEs in the Southeast Asian sector was anti-correlated with the solar cycle and asymmetric characteristics. We hope that this analytical information will be useful for future HF and VHF communications design in the Southeast Asia region.
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    Comparative Study of the Equatorial Plasma Bubbles using VHF Radar Images and Spatial ROTI Maps at Low-Latitude Region
    (2023-01-01)
    Tongkasem, Napat
    ;
    Myint, Lin M.M.
    ;
    Supnithi, Pornchai
    ;
    Hozumi, Kornyanat
    ;
    Nishioka, Michi
    Equatorial Plasma Bubbles (EPBs) depict electron density depletion region originating at the bottom side of the F layer in the ionosphere. The EPBs are often observed in the low latitude region after post-sunset period, particularly, in equinoctial months. Since EPBs have a negative impact on high-precision positioning techniques, degrading convergence time and accuracy, it is essential to study the spatial variations of EPBs during their lifetime. In this work, we develop 2-D temporal-spatial maps based on the rate of change TEC change (ROTI) index analyzed from pseudorange information in a GNSS receiver network over Thailand. The area covers the magnetic equatorial and low-latitude regions including equatorial ionosphere anomaly (EIA). Using 2-D ROTI maps (longitude vs latitude), two types of ROTI keograms (time vs latitude and time vs longitude), we analyze the spatial and temporal changes of recent EPB events. Complementing this analysis, we propose to jointly anlayze the VHF radar images at Prachomklao Chumphon VHF radar station (Lat:10.72 N, Lon: 99.37, Magn. Lat: 1.34). The radar system can scan the ionosphere from geographic latitude 0° N to 20° N and from 140 to 860 km altitude range. The results show that with the three types of data methods, characterizations, speed, velocity and occurrences of EPB are obtained.
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    Automatic classification of spread‐F types in ionogram images using support vector machine and convolutional neural network
    (2024-12-01)
    Benchawattananon, Phongsachot
    ;
    Siritaratiwat, Apirat
    ;
    Supnithi, Pornchai
    ;
    Nishioka, Michi
    ;
    Perwitasari, Septi
    An ionogram image serves as a valuable data for examining the ionospheric bottom side characteristics and variabilities. Spread-F is indicated or identified by plasma irregularity in the ionospheric region. Diffused echo in the ionogram images particularly pose challenges for efficient interpretation required in further applications. An automatic classification of spread-F is presented in this study. Ionogram images are automatically classified using preprocessing techniques to improve the classification performance. In this study, the classification is designed by two machine learning algorithms, including support vector machine (SVM) and convolutional neural network (CNN). The CNN model with preprocessing technique outperforms the SVM alternative based on 4,692 labelled ionogram images from the FMCW-type ionosonde at Chumphon station, Thailand. The model successfully classified clear, frequency spread-F (FSF), range spread-F (RSF), strong spread-F (SSF), and unidentified class with an accuracy of 98.0%, 85.1%, 90.7%, 66.7%, and 99.2%, respectively. The proposed automatic classification models achieved to classify classes of ionogram images. In addition, the image filtering and data preprocessing are useful with ionogram images for improving the model classification performance. Graphical Abstract: (Figure presented.)
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    Clustering of Ionospheric Irregularities based on Spatiotemporal ROTI Keogram Images
    (2024-01-01)
    Mutasov, Gleb
    ;
    Min Myint, Lin Min
    ;
    Supnithi, Pornchai
    ;
    Budtho, Jirapoom
    ;
    Tongkasem, Napat
    Ionospheric irregularities associated with Equatorial plasma bubbles (EPB) can significantly impact navigation and communication systems. Therefore, their occurrences need to be studied and predicted. To solve the prediction problem, it is necessary to identify types of spatiotemporal characteristics as reference points for the predictive model. This work employs unsupervised machine learning algorithms to identify types of ionospheric irregularities due to EPB using the rate of total electron content index (ROTI) keograms. Two machine learning methods: two models, the Gaussian mixture model (GMM), and k-means, are considered. Comparative analysis is performed, and the optimal number of clusters is estimated using one classical, k-means and one additional - repeatability score, introduced in this work metric. The optimal GMM model successfully classifies three types of irregularity patterns offering valuable insights for the development of an effective EPB prediction model and enhancing our understanding of ionospheric behavior.