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, Australian Centre for Geomechanics, Perth, pp. 1521-1530, https://doi.org/10.36487/ACG_repo/2025_105
Hazard mitigation and risk reduction are becoming increasingly important for mining operations as highlighted by recent catastrophic failures of tailings dams worldwide. These events have focused industry attention on the importance of developing and implementing effective monitoring strategies on all mine sites.
Pushed by the increasing requirements of the mining industry, monitoring services are rapidly evolving to provide tools and methods to identify slope instabilities and manage the associated risks, pointing to the importance of a synergistic use of in situ instruments and remote sensing data. In particular, satellite imagery and InSAR displacement maps are becoming a standard tool to implement a robust and repeatable monitoring program. InSAR has been revealed to be an easy-to-integrate companion of in situ monitoring sensors, such as ground-based radars, Robotic Total Stations and geotechnical instruments, and has proven itself as an effective technology for monitoring block caving induced subsidence and instabilities over large infrastructure such as tailings dams, providing a unique synoptic view which cannot be obtained by means of in situ observations.
Limitations of InSAR are currently related to the frequency of acquisition of satellite sensors, as well as the limited spatial resolution of displacement data when using sensors designed for monitoring large areas. While high spatial resolution (1 × 1 m) can be achieved on small areas using commercial sensors, the current sampling frequency of displacement data is at best measured in several days, severely limiting the effectiveness of this tool for feeding early-warning systems.
In this scenario, new constellations of radar sensors are being launched and will shortly become available. This article aims to provide a comprehensive overview of the potential impact on mining monitoring services with a new generation of microsatellites focusing on active radar sensors. Designed to provide high-resolution radar imagery, these data sources will be operational day and night, independent of weather conditions, and allow much more accurate monitoring. With daily updates, InSAR products will see a strong improvement in their ability to detect any changes in displacement trends, allowing operators to develop more effective earlywarning systems based on time series analysis. The use of machine-learning and pattern recognition algorithms over hundreds of assets will make it possible to significantly increase the level of knowledge on slope instability, eventually leading to significant risk reduction.
Keywords: satellite InSAR, monitoring, TSF monitoring
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