Development of a advanced InSAR atmospheric correction method by fusing GNSS observation and numerical atmospheric modeling

2023 Fiscal Year Final Research Report

• Project/Area Number: 21K14006
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 17040:Solid earth sciences-related
• Research Institution: University of Tsukuba
• Principal Investigator: Kinoshita Yohei 筑波大学, システム情報系, 助教 (90750703)
• Project Period (FY): 2021-04-01 – 2024-03-31
• Keywords: InSAR / 大気伝搬遅延 / GNSS / 数値気象モデル / 高精度化

Outline of Final Research Achievements

Synthetic aperture radar interferometry (InSAR), which can detect surface displacement distribution with centimeter to millimeter accuracy, often suffer from the existence of Earth's atmosphere through the microwave propagation delay effect, resulting in the limitation of InSAR observation accuracy.In this study I developed a new correction method for InSAR atmospheric delay noise using GNSS atmospheric observatioin information. The developed model showed higher effectiveness than traditional delay correction methods. Moreover, to improve the applicability of the developed model, I incorpolated a global atmospheric model ERA5 into the developed model (I call it as the hybrid correction model). The hybrid correction model showed same noise reducibility as the GNSS-based developed model, although the hybrid correction model can be applied everywhere even if there are no GNSS stations.

Free Research Field

固体地球物理学

Academic Significance and Societal Importance of the Research Achievements

本研究で開発したInSAR大気ノイズ補正手法は従来の補正手法を上回る補正効果を示しており、これによりこれまで観測精度の制約により検出されなかった微小地表面変位シグナルの検出を実現できる可能性がある。具体例として、スロー地震現象の一つであるスロースリップイベント（SSE）、年間ミリメートル程度の変位量を持つ非地震性の活断層運動、変位分布が地形と相関することの多い山体での火山活動などにおいて、未発見の地表面変位シグナル検出に貢献できる。