10:45 AM - 12:15 PM
[SVC31-P03] Accuracy Validation of Kinematic Positioning for Real-Time Analysis of Multi-GNSS Observation Data at Mt. Usu
Keywords:Mt. Usu, GNSS observation, RTK
Mt. Usu is an active volcano located southwest of Hokkaido, Japan. The volcano has erupted at approximately 30-year intervals and is feared to erupt soon because 23 years have passed since the latest eruption in 2000. All four eruptions since the 20th century occurred at different locations. However, it was difficult to predict the location of eruptions in past eruptions.
The precursor of tens of cm-scale ground deformation has been observed before past eruptions (Takahashi et al., 2002; Okazaki et al., 2002). If we could estimate the location of deformation source in quasi-real time the eruption site might be predicted.
This study aims to construct a real-time crustal deformation monitoring system to predict the eruption site of the next eruption of Mt. Usu by capturing ground deformation preceding the eruption through real-time analysis of GNSS observation data and estimating the source in quasi-real time based on the ground deformation.
We have established a multi-GNSS observation network using u-blox ZED-F9P receiver modules. The network consists of 16 new stations and ten existing ones. We plan to calculate the position of 25 stations with one reference station in real-time kinematic (RTK) positioning using RTKLIB 2.4.3 (Takasu, 2020).
In this presentation, we will discuss the analysis strategy of RTK positioning and the observation error as a preliminary preparation for constructing the real-time monitoring system. We used the carrier phase data recorded during two weeks of temporary observation in 2022 at 16 new stations. The reference station is about 11 km away from the summit of Mt. Usu. We obtained the kinematic positioning solution using 1-sec sampling data. To validate the observation error, we calculated the mean and maximum value of the hourly and three-hourly standard deviation of the positioning results for each station. The system can receive five types different GNSS: GPS, GLONASS, Galileo, BeiDou, and QZSS. We investigated which combination of GNSS can provide the best solution by the integer ambiguity fix rate and standard deviation. As a result, we obtained the stable ambiguity fix rate estimation and the smallest standard deviation from the analysis with the four GNSS excluding GLONASS. Besides, we investigated which minimum elevation angles (15º, 20º, and 25º) can provide a good positioning solution, and the analysis with 20º provided the best solution.
The analysis of 24 hours of observation data for each station with the four satellite systems and 20º as a minimum elevation angle showed that the average hourly standard deviation was 3.5-7 mm horizontally and 7-13 mm vertically at each station. We obtained the maximum value at each stations as of 7-17 mm horizontally and 15-42 mm vertically. The mean 3-hourly standard deviations were 4-8 mm horizontally and 8-14 mm vertically, and the maximum values were 5-13 mm horizontally and 14-30 mm vertically.
Here, when the expected displacement before eruptions exceeded three times the maximum standard deviation, we assumed the displacement could be detected by the new system. The observable displacement in one hour is approximately 50 mm horizontally and 125 mm vertically. Similarly, the observable displacement in 3 hours is approximately 40 mm horizontally and 90 mm vertically. These results suggest that the real-time positioning with our GNSS network can capture the ground deformation with several hundred mm in six hours, as observed in the 2000 eruption (e.g., Takahashi et al., 2002; Okazaki et al., 2002).
It needs to verify more detailed analysis strategies to improve the positioning accuracy, selecting satellites based on the Signal-Noise-Ratio of the satellite signals to detect ground deformation in a shorter period.
The precursor of tens of cm-scale ground deformation has been observed before past eruptions (Takahashi et al., 2002; Okazaki et al., 2002). If we could estimate the location of deformation source in quasi-real time the eruption site might be predicted.
This study aims to construct a real-time crustal deformation monitoring system to predict the eruption site of the next eruption of Mt. Usu by capturing ground deformation preceding the eruption through real-time analysis of GNSS observation data and estimating the source in quasi-real time based on the ground deformation.
We have established a multi-GNSS observation network using u-blox ZED-F9P receiver modules. The network consists of 16 new stations and ten existing ones. We plan to calculate the position of 25 stations with one reference station in real-time kinematic (RTK) positioning using RTKLIB 2.4.3 (Takasu, 2020).
In this presentation, we will discuss the analysis strategy of RTK positioning and the observation error as a preliminary preparation for constructing the real-time monitoring system. We used the carrier phase data recorded during two weeks of temporary observation in 2022 at 16 new stations. The reference station is about 11 km away from the summit of Mt. Usu. We obtained the kinematic positioning solution using 1-sec sampling data. To validate the observation error, we calculated the mean and maximum value of the hourly and three-hourly standard deviation of the positioning results for each station. The system can receive five types different GNSS: GPS, GLONASS, Galileo, BeiDou, and QZSS. We investigated which combination of GNSS can provide the best solution by the integer ambiguity fix rate and standard deviation. As a result, we obtained the stable ambiguity fix rate estimation and the smallest standard deviation from the analysis with the four GNSS excluding GLONASS. Besides, we investigated which minimum elevation angles (15º, 20º, and 25º) can provide a good positioning solution, and the analysis with 20º provided the best solution.
The analysis of 24 hours of observation data for each station with the four satellite systems and 20º as a minimum elevation angle showed that the average hourly standard deviation was 3.5-7 mm horizontally and 7-13 mm vertically at each station. We obtained the maximum value at each stations as of 7-17 mm horizontally and 15-42 mm vertically. The mean 3-hourly standard deviations were 4-8 mm horizontally and 8-14 mm vertically, and the maximum values were 5-13 mm horizontally and 14-30 mm vertically.
Here, when the expected displacement before eruptions exceeded three times the maximum standard deviation, we assumed the displacement could be detected by the new system. The observable displacement in one hour is approximately 50 mm horizontally and 125 mm vertically. Similarly, the observable displacement in 3 hours is approximately 40 mm horizontally and 90 mm vertically. These results suggest that the real-time positioning with our GNSS network can capture the ground deformation with several hundred mm in six hours, as observed in the 2000 eruption (e.g., Takahashi et al., 2002; Okazaki et al., 2002).
It needs to verify more detailed analysis strategies to improve the positioning accuracy, selecting satellites based on the Signal-Noise-Ratio of the satellite signals to detect ground deformation in a shorter period.