固体地球科学(S)
セッション小記号 計測技術・研究手法(TT)
セッションID S-TT50
タイトル 和文 稠密多点GNSS観測が切り拓く地球科学の新展開
英文 New Frontiers in Earth Science Pioneered by Dense GNSS Observation Networks
タイトル短縮名 和文 稠密多点GNSS
英文 Dense GNSS Networks: New Earth Insights
代表コンビーナ 氏名 和文 太田 雄策
英文 Yusaku Ohta
所属 和文 東北大学大学院理学研究科附属地震・噴火予知研究観測センター
英文 Research Center for Prediction of Earthquakes and Volcanic Eruptions, Graduate School of Science, Tohoku University
共同コンビーナ 1 氏名 和文 西村 卓也
英文 Takuya NISHIMURA
所属 和文 京都大学防災研究所
英文 Disaster Prevention Research Institute, Kyoto University
共同コンビーナ 2 氏名 和文 藤田 実季子
英文 Mikiko Fujita
所属 和文 国立研究開発法人 海洋研究開発機構
英文 Japan Agency for Marine-Earth Science and Technology
共同コンビーナ 3 氏名 和文 大塚 雄一
英文 Yuichi Otsuka
所属 和文 名古屋大学宇宙地球環境研究所
英文 Institute for Space-Earth Environmental Research, Nagoya University
共同コンビーナ 4 氏名 和文 木下 陽平
英文 Yohei Kinoshita
所属 和文 筑波大学
英文 University of Tsukuba
発表言語 E
スコープ 和文
The Global Navigation Satellite System (GNSS) is an observation tool with high temporal resolution that enables monitoring of crustal deformation caused by earthquakes and volcanic activity, the dynamics of water vapor in the troposphere, and spatiotemporal variations in the ionosphere induced by solar activity and other surface phenomena.
In Japan, the Geospatial Information Authority of Japan (GSI) has operated GEONET since 1996, now comprising more than 1,300 GNSS observation stations spaced about 20-30 km apart, which has contributed significantly to advancing our understanding of a wide range of Earth science phenomena.
In recent years, rapid technological developments such as automated driving and drones have emerged. GNSS forms the foundation of the navigation technology that supports these applications. In addition to conventional metric positioning, centimeter-level real-time positioning using carrier-phase measurements is becoming widely available. Mobile network operators have begun deploying their own GNSS observation networks across Japan as reference sites, and their applications to Earth science have recently begun.
In this session, we discuss the usability and challenges of dense GNSS observation networks and explore a broad range of Earth science topics that can be addressed using dense GNSS observation data. While motivated by Japan's experience, we explicitly welcome submissions from outside Japan, including international case studies, comparative analyses, and cross-regional perspectives.
英文
The Global Navigation Satellite System (GNSS) is an observation tool with high temporal resolution that enables monitoring of crustal deformation caused by earthquakes and volcanic activity, the dynamics of water vapor in the troposphere, and spatiotemporal variations in the ionosphere induced by solar activity and other surface phenomena.
In Japan, the Geospatial Information Authority of Japan (GSI) has operated GEONET since 1996, now comprising more than 1,300 GNSS observation stations spaced about 20-30 km apart, which has contributed significantly to advancing our understanding of a wide range of Earth science phenomena.
In recent years, rapid technological developments such as automated driving and drones have emerged. GNSS forms the foundation of the navigation technology that supports these applications. In addition to conventional metric positioning, centimeter-level real-time positioning using carrier-phase measurements is becoming widely available. Mobile network operators have begun deploying their own GNSS observation networks across Japan as reference sites, and their applications to Earth science have recently begun.
In this session, we discuss the usability and challenges of dense GNSS observation networks and explore a broad range of Earth science topics that can be addressed using dense GNSS observation data. While motivated by Japan's experience, we explicitly welcome submissions from outside Japan, including international case studies, comparative analyses, and cross-regional perspectives.
発表方法 口頭および(または)ポスターセッション
時間 講演番号 タイトル 発表者
口頭発表 5月29日 AM1
9:00 - 9:15 STT50-01 CSESS: Enabling Geoscience with SoftBank’s Ultra-Dense GNSS Reference Network 太田 雄策
9:15 - 9:30 STT50-02 Water vapor distributions around heavy rainfalls estimated by the tomography method 瀬古 弘
9:30 - 9:45 STT50-03 Assessing the impact of dense GNSS network data for atmospheric delay correction in InSAR and its time series 木下 陽平
9:45 - 10:00 STT50-04 Traveling Ionospheric Disturbances Observed During the 2024 Typhoon Shanshan: Effects of Atmospheric Waves and Electro-dynamical Forces Junxian Fu
10:00 - 10:15 STT50-05 稠密全球測位衛星システム受信機観測網を用いた三次元トモグラフィーによる伝搬性電離圏擾乱の研究 石田 志音
10:15 - 10:30 STT50-06 日本における全球測位衛星システム受信機観測網を用いた電離圏擾乱の衛星測位への影響 中村 京誠
口頭発表 5月29日 AM2
10:45 - 11:00 STT50-07 2025年7月のMw8.8カムチャッカ半島地震に伴う電離圏擾乱:震源直上および遠方場におけるGNSS-TEC観測 日置 幸介
11:00 - 11:15 STT50-08 Advances in Ionospheric Seismology using the Japanese GNSS network Maletckii Boris
11:15 - 11:30 STT50-09 Kinematic GNSS Accuracy in an Integrated Public–Private Ultra-Dense Network: GEONET and SoftBank Reference Stations 伊藤 嘉秋
11:30 - 11:45 STT50-10 GNSS-based modeling of pressure source evolution during the 2024 Mt. Iwate unrest event Ava Shetina
11:45 - 12:00 STT50-11 Transient crustal movement synchronized with the 2026 seismic swarm in Northern Hokkaido, Japan 大園 真子
12:00 - 12:15 STT50-12 Detailed distribution of interseismic deformation revealed by dense integrated GNSS networks in the Keihanshin area 西村 卓也
講演番号 タイトル 発表者
ポスター発表 5月29日 PM3
STT50-P01 A weighting strategy considering inter-satellite separation for regional VTEC ionosphere models in PPP performance Feng-Yu Chu
STT50-P02 超稠密GNSS受信機網を用いたスポラディックE層の複数事例にわたる高時空間分解能解析 ―前線状構造とパッチ状構造― 田納 俊太
STT50-P03 Case Studies of Midnight Medium-Scale Traveling Ionospheric Disturbances in Japan using Dense GNSS Observation Networks 傅 維正
STT50-P04 Characteristics of spatially long-wavelength noise based on the ultra-dense GNSS observation 岡田 悠太郎
STT50-P05 地殻変動データに基づく2020年飛騨山脈の群発地震活動駆動源の推定 川上 大輔
STT50-P06 Ultra-Dense Public–Private GNSS Networks Reveal Japan’s Crust in Fine Detail 太田 雄策
STT50-P07 Vertical Crustal Deformation in Japan, Estimated from an Integrated Public–Private GNSS Network 大舘 未来
STT50-P08 Atmospheric Stability Estimation: Localized Thunderstorm in Tokyo, July 20, 2024 藤田 実季子