干渉SAR時系列解析とWebGIS・Webアプリによる可視化手法の紹介

抄録

Ground deformation and road subsidence in urban areas are critical social concerns that require effective monitoring and infrastructure maintenance. Time-series Interferometric Synthetic Aperture Radar (InSAR) is a powerful technology capable of detecting continuous minute surface displacements over wide areas. However, it remains challenging to utilize the resulting multi-dimensional point cloud data in practical operations because conventional static drawings and two-dimensional geographic information system (GIS) environments cannot effectively display or share the integrated spatial and temporal information.

This paper introduces a practical approach to ground deformation monitoring and visualization. First, a permanent scatterer InSAR (PSInSAR) time-series analysis was conducted on the urban road subsidence incident that occurred in Chofu City, Tokyo, in October 2020. Utilizing Sentinel-1 C-band synthetic aperture radar (SAR) data (2019–2021) combined with a 10-meter digital elevation model (DEM), 2.5-dimensional (2.5-D) analysis was performed by integrating ascending and descending orbits to separate displacements into quasi-upward and quasi-eastward components. The analysis successfully captured a localized quasi-upward subsidence of up to approximately 15 mm and distinctive opposing quasi-eastward horizontal movements concentrated around the subsidence area from September 2020, demonstrating the high accuracy and spatial-temporal resolution of the method.

Second, to overcome information-sharing barriers among diverse stakeholders, this paper presents two intuitive visualization solutions: an online WebGIS environment utilizing ArcGIS Dashboards and a secure, offline client-side Web application built with Leaflet.js. The WebGIS dashboard integrates multi-dimensional datasets into a code-free interactive interface, allowing non-experts to instantly view displacement time-series graphs linked to specific geographic points. Meanwhile, the client-side Web application enables standalone high-security data analysis—including attribute-based color mapping, dynamic threshold screening, and on-the-fly linear regression—directly within standard web browsers without data leakage risks.

In conclusion, integrating advanced time-series InSAR analysis with interactive visualization platforms and high-quality geospatial data significantly enhances risk assessment, disaster mitigation, and infrastructure lifecycle management.