Nationwide, Operational Sentinel-1 Based InSAR Monitoring System in the Cloud for Strategic Water Facilities in Hungary

Abstract

The intensive development of both interferometric technology and sensors in recent years allows Interferometric Synthetic Aperture Radar (InSAR)-based applications to be accessible to a growing number of users. InSAR-based services now cover entire countries and soon even the whole of Europe. These InSAR systems require massive amounts of computer processing power and significant time to generate a final product. Most, if not all, of these projects have a limited “monitoring component”, aimed at historical analysis but are rarely, if ever, updated. Consequently, the results do not necessarily meet every purpose or specific user requirement. It is now clear that the increasing computing capacity and big data provided by the sensors have initiated the development of new InSAR services. However, these systems are only useful when linked to specific real-world operational problems. Continuous monitoring of a country’s ageing water management infrastructure has become an increasingly critical issue in recent years, in addition to the threats posed by climate change. Our article provides a comprehensive overview of a nationwide, dedicated, operational InSAR application, which was developed to support the operational work of the Hungarian Disaster Management Service (HDMS). The objective was to provide monthly monitoring of 63 water facilities, including 83 individual objects, distributed throughout Hungary, in combination with the development of a near real-time warning system. Our work involved the compilation of a completely new InSAR System as a Service (SaaS) which incorporates user requirements, preparatory work, the compilation of the Sentinel-1 automatic processing pipeline, the installation of corner reflectors, a special early warning system, and a dedicated user interface. The developed system can automatically start to evaluate the S1 measurements within 24 h of downloading the data into the system storage forward the results toward the warning system before the next image arrives. Users are provided with detailed information on the stability of 70% of the 83 water facility objects monitored through the dedicated user interface. The additional early warning system currently operates as a preliminary “spatial decision support system”, but the HDMS is willing to make it fully operational over the next few years.

Development of a Proof-of-Concept A-DInSAR-Based Monitoring Service for Land Subsidence

“…Recently, other examples of nationwide A-DInSAR data have been processed to monitor the ground deformations in Greece [22] and Japan [23]. Nationwide and country scale A-DInSAR data are used for several purposes such as strategic water facilities monitoring in Hungary [24], landslide mapping and risk management in Italy [25], railway monitoring in the Netherlands [26], and assessment of areas, population, and households exposed to land subsidence in Mexico [27].…”

Land Subsidence Monitoring and Building Risk Assessment Using InSAR and Machine Learning in a Loess Plateau City—A Case Study of Lanzhou, China

“…The Time Series Interferometric Synthetic Aperture Radar (TS-InSAR) technique has the advantage of all-day, wide-coverage, and low-cost monitoring, with a high temporal resolution and a low engagement level of human resources. It can provide millimeter-level accuracy by processing multiple SAR images, and is widely used in many fields, such as urban subsidence monitoring [13][14][15][16][17], landslide monitoring [18][19][20][21], seismic deformation research [22][23][24][25], mine deformation monitoring [25][26][27][28], and the safety monitoring of water conservancy projects [29][30][31][32]. Among them, the Permanent Scatterer (PS) technique [33][34][35] proposed by Ferreti et al and the Small Baseline Subset (SBAS) technique [36,37] proposed by Berardino et al are the most mature and widely used approaches [38][39][40][41][42].…”