The historical Ukrainian rock-salt mining town of Solotvyno and its environmentally related problems are well-known. A complex monitoring system is needed to evaluate the current situation in order to revitalize the investigated area. In addition to other risks, surface deformation due to undermining is one of the major risks endangering building infrastructure in the inhabited area of the town. These processes are well-known in the area, and damages caused by the surface movement are often recognized. Measurement of the process’s intensity and identification of the impacted area are crucial for any revitalization work. Information on these processes is the most important element of the hazard management and spatial-developmental planning of the town. This study aimed to characterize the long-term surface deformation processes and to identify the spatial and temporal trends and changes of these processes to assist spatial planning. The first step was to understand the surface deformation history from 1992. An InSAR-based assessment of the surface displacement of the undermined Solotvyno area was performed using data from three satellites, namely the ERS, Envisat, and the Sentinel-1, covering the time period between 1992 and 2021. The derived quantitative analysis indicated an intensive surface displacement and subsidence over the mining area. However, these displacements have not been even in the last 30 years of the investigation. The identification of the stabilized areas and recently started movements indicated the dislocation of the processes, which requires adequate actions for geohazard management and strategic planning. The demonstrated technology (InSAR) has the potential to set up an appropriate alarm system and provides an automated mechanism for continuous risk detection. A complex systems development is able to significantly reduce the geohazards over the unstable built-up zones.
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.
Since 2014, Sentinel-1 (S1) Synthetic Aperture Radar (SAR) data have become an important source in the field of displacement detection thanks to regular acquisitions and 7.5 years of temporal coverage at global level. Despite the increasing number of publications on the role of S1 in landslide detection, there is still a need for research to further clarify the capabilities of the sensor and the applicable image analysis techniques. Previous studies have successfully exploited high-resolution ALOS-PALSAR image-based intensity and coherence analysis at the 2018 Hokkaido landslides. Nevertheless, they expressed a clear need to analyse the capabilities of other sensors (such as S1). This raises the question: Do we need SAR imagery with higher spatial resolution (such as ALOS-PALSAR) or are freely available S1 imagery also suitable for rapid landslide detection? The S1 images could provide suitable material for a comparative analysis and could answer the aforementioned question. Therefore, 17 ascending and 19 descending S1 images were analysed to test S1 accuracy on landslide detection. Multitemporal analyses of both intensity and coherence were performed along with coherence differences, multitemporal features (MTF) and MTF differences of coherence images. In addition, the spatial analysis of the classification results was also evaluated to highlight the potential of S1 coherence analysis. S1 was found to have limitations at the site, as single coherence differences provided low-quality results. However, the results were significantly improved by calculating the MTF on coherence and almost reached the success rate of the ALOS-PALSAR-based coherence analysis, even though the improvement of the results with intensity was not possible. Half of the false positives were identified in the 30–45-m buffer zone of the agreement, underlining that the spatial resolution of the S1 is not appropriate for accurate landslide detection. Only an approximation of the landslide-affected area can be given with considerable overestimation. Due to the inclusion of post-event images, the sensor is not perfectly applicable for rapid detection purposes here.
Неразрушающий контроль зданий и сооружений является актуальной проблемой в современном строительстве. Несмотря на то, что за последние десятилетия было разработано много измерительных методов, все же остаются некоторые пробелы в системе оценки состояния зданий и сооружений. Одна из основных проблем заключается в том, что измеряемые параметры оцениваются лишь время от времени. Существует ограниченное количество доступных методов, которые могут обеспечить непрерывный мониторинг технического состояния строительных сооружений и предоставить информацию об их устойчивости во временном ряду. Основная цель данной статьи - представить диагностический метод, который может преодолеть упомянутые недостатки, сочетая периодические неразрушающие измерения с непрерывным мониторингом, получаемым путем применения спутникового дистанционного зондирования. Радар с синтезированной апертурой (SAR) имеет много преимуществ, которые стоит учитывать инженерам-строителям в практике оценки устойчивости зданий и сооружений. Наша задача - дать представление о теории интерферометрических радаров с синтезированной апертурой (InSAR) и продемонстрировать их совместное применение с другими методами оценки состояния зданий на конкретных примерах. Эффективность предложенной методики была продемонстрирована сравнением результатов смещения водонапорной башни, полученных с помощью мониторинга InSAR, традиционной геодезической съемки и численного анализа.
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