SAR Remote Sensing for Mining

 SAR Remote Sensing for Mining

SAR remote sensing methods have evolved to be among the most useful monitoring techniques in modern mining. This article describes some of the newest technologies for keeping mines safe for both mining operators as well as the communities and landscapes they exist in.

Mining is an important economic activity providing many of the natural resources used in modern society. Mining is a risky undertaking, so risk management is a key activity in mining operations around the world. The stability of mines is constantly evaluated, to avoid risks to the local infrastructure and to the humans living and working at the mine site and in the surrounding area. Still we too often read news about miners trapped in collapsed mines or environmental disasters like landslides or floods due to mining activities.

Some types of mines (source: Reddit)

Surface mining, using large open pits in the Earth’s surface (see header image) is the predominant mine exploitation method worldwide. Open pit mining involves mechanical extraction of resources. Open pit mining is best for extracting near-surface deposits or mining for ore that has a low stripping ratio, meaning there is relatively little waste material that is mined together with the desired ore. Open pit mines generally require a large capital investment, but result in high productivity, low operating costs and good safety conditions, when compared to underground mining methods.

Underground mining and tunnelling activities (see below image) can produce extensive subsidence of the ground surface, which in severe cases can have serious consequences. Excessive subsidence will halt production and create severe safety issues, can damage above-ground structures and lead to extensive project delays, in addition to causing risks for the local environment and communities.

Underground mine, zone of crosscut (source: Mining – Molecular Products)

InSAR for monitoring ground subsidence

SAR Interferometry (InSAR) remote sensing solutions provide wide coverage and high density information about the stability of an area. It also allows to assess historical deformation, by processing satellite data archives going back to the early 1990s. Furthermore, recent advances in processing algorithms have significantly reduced computing time and the advent of newer satellites with increased spatial resolution and acquisition frequency have increased information density, to monitor both slow and fast movements.

PSI and SqueeSAR

In addition to traditional SAR remote sensing data analysis methods, there are two analysis techniques that are especially useful for monitoring surface subsidence in mining areas:

Permanent Scatterer Interferometry (PSInSAR)

PSI techniques were first published in 1999 when the Polytechnic University of Milan (POLIMI) developed and patented its Permanent Scatterer Interferometry (or PSInSAR) algorithm.

The PSI or PSInSAR technique focuses on the use of phase information from points that maintain their backscatter properties over time, so permanent structures that maintain their integrity over time and can be recognised on SAR images, like houses or large boulders. The selection criterion of the PSI is directed towards the temporal stability of their amplitude or stability of the phase of the signal.

The principle of PSInSAR explained (image: TRE Altamira)

Other specialists use as a selective criterion the spatial coherence of each interferogram with small baselines. A drawback of this method is that it requires a large amount of images of a single location. The number of acquisitions should be at least 20 images with a regular temporal separation, with 30 images being an optimal number.

This approach is usually applied to urban areas or regions with objects that have a high radiometric and phase stability, allowing to calculate displacements in the order of a few millimetres. In these situations PSInSAR generates more accurate measurements than other DInSAR techniques.


SqueeSAR is an algorithm specifically provided by the TRE Altamira company. It provides a significantly increased coverage of ground points, especially over non-urban areas. The difference with PSInSAR is that SqueeSAR continues to identify permanent scatterers (PS) (large fixed objects), but it also exploits spatially distributed scatterers (DS). Whilst PS usually correspond to man-made objects like buildings, DS are typically identified from homogeneous ground, scattered outcrops, debris flows, non-cultivated lands, and desert areas.

In conclusion, time series analysis allows to reduce errors in the interferometric phase caused by various factors like atmospheric anomalies, orbit errors, or loss of coherence measurements, improving the accuracy of the deformation measurement.

TRE Altamira

An example of monitoring of stability of an open pit mine is offered by TRE Altamira. This self-proclaimed world leader in measuring ground and structural movement from space uses the example of the open pit mine in Bytom City, Poland. This large mine is located in the north-western part of the Upper Silesian Coal Basin in southern Poland. TRE Altamira uses DInSAR techniques to detect short-term fast deformation in the area of this mine.

Mining activities in this area are carried out by so-called longwall mining. The excavated coal layer is 2.5 metres thick, 250 to 400 metres long, and about 680 meters deep. Historical subsidence of the surrounding area of nearly 300 square kilometres has been measured of up to 27 metres over 33 years.

SqueeSAR cumulative displacement overlain on the DInSAR results (source: TRE Altamira)

The deformation values obtained with this method allows us to think in the management of the risk associated with the deformation processes found in the area, considering the existence of a population and an infrastructure that could be affected by the subsidence processes. The timely mapping of the extent and magnitude of surface movement is usually one of the main challenges faced by geotechnical managers in these cases.

Series about SAR Remote Sensing

This article is part of a series of articles on Groundstation.Space on the applications of satellite-based Synthetic Aperture Radar (SAR) remote sensing, written by our SAR expert author Gabriela Quintana Sanchez, with editing support by Remco Timmermans.

Find all articles in this series here.

Gabriela Quintana Sánchez

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