Jamjareegulgarn, Punyawi

Preferred name

Alternative Name

Jamjareegulgarn, P.

Main Affiliation

KMITL Prince of Chumphon Campus

punyawi.ja@kmitl.ac.th

Now showing 1 - 10 of 21

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Improvement of Real-Time Kinematic Positioning Using Kalman Filter-Based Singular Spectrum Analysis During Geomagnetic Storm for Thailand Sector
(2023-01-01)
Srisamoodkham, Worachai
;
Ansari, Kutubuddin
;
Jamjareegulgarn, Punyawi
The ionospheric error is the largest error source of positioning, especially when electron density becomes high during geomagnetic storms. Real-time kinematic (RTK) positioning during the storm time often has higher fluctuation and noise errors in positioning. Therefore, in this work, a technique based on Kalman filter with implementation of singular spectrum analysis (namely KF-SSA) is anticipated for RTK positioning. The RTK drone data are collected around 50 min of interval (7.37 AM to 8.28 AM) on May 12, 2021, with respect to a base station located at 13.84° N, 100.29° E. The RTK positioning tests have been done to determine the positioning accuracy of the proposed algorithm. The simulated results reveal that SSA implication with KF showed very high-precision estimates and improves the positioning accuracy.
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Quasi zenith satellite system-reflectometry for sea-level measurement and implication of machine learning methodology
(2022-12-01)
Ansari, Kutubuddin
;
Seok, Hong Woo
;
Jamjareegulgarn, Punyawi
The tide gauge measurements from global navigation satellite system reflectometry (GNSS-R) observables are considered to be a promising alternative to the traditional tide gauges in the present days. In the present paper, we deliver a comparative analysis of tide-gauge (TG) measurements retrieved by quasi-zenith satellite system-reflectometry (QZSS-R) and the legacy TG recordings with additional observables from other constellations viz. GPS-R and GLONASS-R. The signal-to-noise ratio data of QZSS (L1, L2, and L5 signals) retrieved at the P109 site of GNSS Earth Observation Network in Japan (37.815° N; 138.281° E; 44.70 m elevation in ellipsoidal height) during 01 October 2019 to 31 December 2019. The results from QZSS observations at L1, L2, and L5 signals show respective correlation coefficients of 0.8712, 0.6998, and 0.8763 with observed TG measurements whereas the corresponding root means square errors were 4.84 cm, 4.26 cm, and 4.24 cm. The QZSS-R signals revealed almost equivalent precise results to that of GPS-R (L1, L2, and L5 signals) and GLONASS-R (L1 and L2 signals). To reconstruct the tidal variability for QZSS-R measurements, a machine learning technique, i.e., kernel extreme learning machine (KELM) is implemented that is based on variational mode decomposition of the parameters. These KELM reconstructed outcomes from QZSS-R L1, L2, and L5 observables provide the respective correlation coefficients of 0.9252, 0.7895, and 0.9146 with TG measurements. The mean errors between the KELM reconstructed outcomes and observed TG measurements for QZSS-R, GPS-R, and GLONASS-R very often lies close to the zero line, confirming that the KELM-based estimates from GNSS-R observations can provide alternative unbiased estimations to the traditional TG measurement. The proposed method seems to be effective, foreseeing a dense tide gauge estimations with the available QZSS-R along with other GNSS-R observables.
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Singular spectrum analysis of GPS derived ionospheric TEC variations over Nepal during the low solar activity period
(2020-04-01)
Ansari, Kutubuddin
;
Panda, Sampad Kumar
;
Jamjareegulgarn, Punyawi
Accurate modeling of ionospheric total electron content (TEC) is an important aspect for mitigating the threats of trans-ionospheric delay error in satellite communication, earth observation, space-based navigation, timing applications as well as space weather forecasting services. In recent years, singular spectrum analysis (SSA) has been proved to be a powerful technique giving a relatively accurate estimate in time-series analysis comparable to the contemporary methods. In the current study, the SSA has been implemented on the GPS-derived TEC during the low solar activity year of 2017 over Nepal region which locates itself almost in the vicinity of low-latitudes being sandwiched between India and Tibet, China. The country foresees an explicit investigation and modeling of ionospheric TEC variations and corresponding delay error to precisely accomplish the space-based trans-ionospheric applications. The semi-annual variability of TEC with higher magnitudes during equinoctial seasons and lower values during solstice seasons is clearly noticed in the diurnal plots which are further substantiated by the trajectory matrix of time-series. The decomposed modes in the principal component analysis (PCA) signifies diurnal (first), semidiurnal (second), semiannual (third), monthly (fourth) with higher orders representing associated noise errors in the signals. Correlation coefficients (CC) between the reconstructed and observed time-series demonstrates the SSA method could be a successful tool for forecasting the TEC series over the region. The results are compared with empirical global ionospheric maps (GIMs) and IRI-Plas 2017 models during different seasons, emphasizing the suitability of SSA technique for relatively better precise TEC forecasting over the region.
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Publisher Correction: Quasi zenith satellite system-reflectometry for sea-level measurement and implication of machine learning methodology (Scientific Reports, (2022), 12, 1, (21445), 10.1038/s41598-022-25994-6)
(2023-12-01)
Ansari, Kutubuddin
;
Seok, Hong Woo
;
Jamjareegulgarn, Punyawi
In the original version of this Article a previous rendition of Figure 6 was published. The original Figure 6 and accompanying legend appear below. The original Article has been corrected.
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Positioning Comparison Using GIM, Klobuchar, and IRI-2016 Models During the Geomagnetic Storm in 2021
(2022-01-01)
Srisamoodkham, Worachai
;
Ansari, Kutubuddin
;
Jamjareegulgarn, Punyawi
This paper compares the positioning accuracy obtained from the GIM VTEC, the Klobuchar model, and the IRI-2016 model at Chiang Mai and DPT9 stations, Thailand, during an intense geomagnetic storm of 2021 (on May 12, 2021). The results show that the diurnal variation of the Klobuchar modeled VTECs show the same trend as that of the observed GIM VTECs with the same peaks and the maximum deviation of 22.5% at 05:00 UT. Meanwhile, the IRI2016-predicted VTECs show its peak at 07:00 UT and are not available obviously during 13:00–21:00 UT due to the impact of this intense geomagnetic storm. Most of the ionospheric delays obtained from the Klobuchar model underestimate those of the GIM VTEC, whereas they overestimate those of GIM VTEC during after midnight and pre-sunrise period. At both stations, the mean ionospheric range delays of the GIM VTEC are highest during daytime period while those of the IRI-2016 model are largest during nighttime period. The positioning errors at higher latitude (CHMA station) are larger than those at lower latitude (DPT9 station).
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Effect of Weighted PDOP on Performance of Linear Kalman Filter for RTK Drone Data
(2022-01-01)
Ansari, Kutubuddin
;
Jamjareegulgarn, Punyawi
The study established a theoretical relation between weighted position dilution of precision (WPDOP) and standard deviation (STD) of positioning error ( $\epsilon /\sigma {R})$ derived by linear Kalman filter (KF). The obtained results exposed a rectangular hyperbolic relationship of WPDOP and STD of error. The RTK Drone data were collected around 50 min of interval (07:37 to 08:28 A.M.) on May 12, 2021, with respect to the base station located at 13.841°N; 100.288°E over Thailand region, and a numerical test has been carried out to demonstrate the proposed algorithm. The simulation results verified the theoretical hyperbolic relationship with the distinct flatness of the curve at the base and drone receiver. This different flatness from the experiments was anticipated because of the position errors for the highly nonlinear dynamics motion of the drone receiver while the base receiver is fixed at one location.
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Climate thresholds and yield elasticity of durian, mangosteen, and coffee under hydroclimatic variability in Thailand
(2026-08-01)
Ansari, Kutubuddin
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Tanır Kayıkçı, Emine
;
Jamjareegulgarn, Punyawi
This study examines the empirical relationships between hydroclimatic variability and the yields of durian, mangosteen, and coffee across Thailand using meteorological observations from 56 stations and provincial level yield statistics for 2008 to 2024. An integrated statistical framework was applied, including exploratory correlation analysis, nonlinear quadratic additive modelling, lagged climate response analysis, elasticity estimation, model comparison, mangosteen regional sensitivity analysis, and a Climate Risk Index (CRI). The results show clear spatial gradients in temperature, humidity, and precipitation across the six agroclimatic regions of Thailand, broadly corresponding to regional crop productivity patterns. Annual anomaly analysis indicates that warm and humid years are generally associated with higher durian and mangosteen yields, whereas excessive rainfall and warming are associated with reduced coffee productivity. Pairwise linear correlations between annual climate variables and crop yields are generally weak, suggesting that simple linear models may not fully capture crop climate relationships. Nonlinear modelling indicates approximate empirical temperature turning points near 28.0°C for durian, 27.3°C for mangosteen, and 26.6°C for coffee, with humidity related turning points around 76–78%. Lagged climate response models suggest that multi-year hydroclimatic conditions may influence perennial crop productivity, particularly humidity for durian, precipitation for coffee, and temperature and precipitation for mangosteen. The mangosteen sensitivity analysis shows that humidity and precipitation thresholds are affected by regional composition, especially when marginal production regions are included. The CRI formulation under the equal weight, mangosteen shows the highest rainfall related climate risk signal, while coffee is more sensitive to temperature related risk and durian shows moderate vulnerability to prolonged humid and wet conditions.
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Individual performance of multi-GNSS signals in the determination of STEC over Thailand with the applicability of Klobuchar model
(2022-02-01)
Seok, Hong Woo
;
Ansari, Kutubuddin
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Panachai, Chaiwat
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Jamjareegulgarn, Punyawi
Thailand is situated in the southern low latitude region in the Asian longitude sector having much importance as major portion of southern hemisphere is covered by ocean resulting in a sparse density of ground-based monitoring systems. With the establishment of GNSS monitoring stations across the Thailand and neighboring region, it accentuates the ionospheric variability study in the southern hemisphere in the Asian longitude. Therefore, in the current study, we selected four GNSS station located at different part of the country (i.e., CHMA, DPT9, NKRM, and SRTN) and studied the variations of ionospheric slant total electron content (STEC). Here, the STEC observations are estimated by Klobuchar model (namely, Klobuchar-modeled STEC values) and compared with the Global Ionospheric Map (GIM) STEC values for its validation. As an initial study, the Klobuchar-modeled STEC values obtained from five multi-constellation GNSSs over Thailand region (i.e., GPS, GLONASS, Galileo, BeiDou and QZSS) are computed and compared with the GIM STEC values during the intense geomagnetic storm on May 12, 2021 (DOY 132) and during June 2020 to May 2021 for monthly variations. Moreover, to show the relationships between the proposed Klobuchar-modeled STEC values and the GIM STEC values, the correlation coefficients and the root mean square errors between them are computed. The results showed that among the five multi-constellations of GNSSs, the GIM STEC values frequently overestimate the Klobuchar-modeled STEC values, except the QZSS system with the least differences ranging from −10 TECU to 20 TECU. Also, the correlation coefficient between the proposed Klobuchar-modeled and GIM STEC variations span between 0.87 and 0.89, and their RMSEs range from 10 TECU to 11 TECU, excluding QZSS system with less than 10 TECU. The correlation coefficients of higher than 0.85 can be considered as a good indicator for the applicability of Klobuchar model in practice with multi constellation systems.
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Ionospheric gradients in multi-constellation global navigation satellite system signals onboard UAV using GIM and Klobuchar model over Thailand region
(2026-07-01)
Ansari, Kutubuddin
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Panda, Sampad Kumar
;
Venkatesh, Kavutarapu
;
Jamjareegulgarn, Punyawi
The effects of the ionosphere on Global Navigation Satellite System (GNSS) signals have been a focal point of research nowadays. During adverse ionospheric conditions, ionospheric gradients become more pronounced and disruptive compared to quiet days, potentially leading to increased positioning errors or loss of satellite signal lock. We introduce an ionospheric spatial gradient estimation method to detect the anomalous gradients from multi-constellation GNSS signals (i.e., GPS, GLONASS, and Galileo) signals recorded by the onboard sensor of flying real-time kinematic unmanned aerial vehicle (RTK UAV) over the Thailand region. We employ the Klobuchar model and global ionospheric maps (GIMs) for estimating the slant total electron contents (STECs) and the corresponding ionospheric spatial gradients between base station and rover (RTK UAV) receivers among the studied multi-constellation systems. The results show that the STEC values estimated from IGS-GIM are larger than those computed by Klobuchar model. Such kind of gradient variation cannot show a perfect correlation due to limited accuracy of Klobuchar model parameters. As for our analysis, the ionospheric spatial gradients estimated from GPS satellites are higher than those calculated from GLONASS and Galileo satellites due to the smallest differences between the two successive positions of flying rover estimated from GPS satellites. The outcomes from this study complement the multi-GNSS cooperative strategy for monitoring ionospheric gradients, thereby mitigating the adverse effects in dynamic positioning and navigation solutions over low-latitude regions.
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Decadal and seasonal oceanographic trends influenced by climate changes in the Gulf of Thailand
(2025-06-01)
Lubis, Muhammad Zainuddin
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Ghazali, Muhammad
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Simanjuntak, Andrean V.H.
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Riama, Nelly F.
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Pasma, Gumilang R.
Our study investigates the decadal and seasonal variability of sea surface height (SSH) and sea surface temperature (SST) in the Gulf of Thailand (GoT) using data from CMEMS from 1993 to 2021. We employed statistical analyses utilizing GLM and GAM to assess the variables comprehensively. The reveals a significant upward trend in SSH, increasing from ∼0.79 m in 1993–1998 to ∼0.89 m in 2017–2021, highlighting the impacts of climate change. SST analysis revealed fluctuations, with a maximum reaching ∼30.6 °C in 2019–2020, correlating with climatic events such as El Niño. Our study results at station 1 (near Bangkok) showed that the average SSH in 1998 during strong El Niño years was equal to 0.82 m, while the maximum SST was equal to 29.89 °C. Seasonal patterns indicated SSH peaks in DJF and SON at ∼0.92 m, while SST peaked in spring MAM and summer JJA at ∼30.7 °C. Volume transport analysis showed significant variability, with 0.3634 Sv (0–55 m) at longitude 99°E-107° E and latitude 6° N, indicating complex circulation patterns influenced by bathymetry and wind. Time series analysis revealed an average SSH increase of 0.0038 m/year, with a high pseudo-R-squared of 0.99. Our findings underscore the critical influence of climate variability on oceanographic conditions in the GoT, emphasizing the need for ongoing monitoring to address the implications of rising sea levels and temperature fluctuations. In conjunction with increased SSH, the rising SST heightens the risk of flooding in low-lying areas, exacerbating vulnerabilities for local populations and necessitating adaptive management strategies to mitigate these impacts.

Jamjareegulgarn, Punyawi

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