Satellite Interferometry as a Tool for Early Warning and Aiding Decision Making in an Open-Pit Mine

• Main Authors: Emanuele Intrieri, Tommaso Carla, Paolo Farina, Federica Bardi, Hakki Ketizmen, Nicola Casagli
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
• Subjects: Earth observation; landslide hazard; mapping; monitoring¸ remote sensing
• Online Access: https://ieeexplore.ieee.org/document/8938757/

Slope failures are life-threatening geohazards well-known in the mining industry, where a single accident can endanger workers and cause million dollars' -worth of activity downtime. Therefore, a detailed ground deformation map of an open-pit mine represents a vital planning tool and high-frequency monitoring is pivotal, since false or anticipated alarms may represent a higher impact than missed alarms. This article presents an application of interferometric satellite data from Sentinel-1. The scope of the study is showing the potential of the new generation of satellites for the detection of the boundary, typology, and kinematics of the on-going slope instabilities in open-pit mines. Most notably, this experience discloses how the short revisiting time (six days) permits the implementation of time of failure forecasting methods, which so far were a prerogative of ground-based monitoring systems. Only recently, a few experiences have shown the possibility of (a posteriori) predicting slope failures using displacement time series measured from satellite; the case study here described represents one of such first examples. Moreover, 11 other areas of instability have been detected and classified in terms of subsidence (sediment compaction) or slope failures, based on considerations concerning the acquisition geometry used to detect the movements. The movement vectors along the ascending and descending lines of sight have been combined to compute horizontal and vertical vectors, which have been employed to infer the geometry of the sliding surface of some selected slope instabilities. Despite the advancements of the technique, clear limitations still exist and are discussed in this article.