On the use of ground-based synthetic aperture radar for long-term slope monitoring to support the mine geotechnical team

Authors: Leoni, L; Coli, N; Farina, P; Coppi, F; Michelini, A; Costa, TA; Costa, TAV; Costa, F Download Paper

DOI https://doi.org/10.36487/ACG_rep/1508_58_Farina

Cite As:
Leoni, L, Coli, N, Farina, P, Coppi, F, Michelini, A, Costa, TA, Costa, TAV & Costa, F 2015, 'On the use of ground-based synthetic aperture radar for long-term slope monitoring to support the mine geotechnical team', in PM Dight (ed.), FMGM 2015: Proceedings of the Ninth Symposium on Field Measurements in Geomechanics, Australian Centre for Geomechanics, Perth, pp. 789-796, https://doi.org/10.36487/ACG_rep/1508_58_Farina



Abstract:
Nowadays, ground-based synthetic aperture radar interferometry (GBInSAR) is used internationally as a leading edge tool for the near real time monitoring of slope movements on landslides and open pit mines for both safety-critical or background monitoring purposes. The success of the technology relies mainly on its ability to rapidly measure slope movements with sub-millimetre accuracy over wide areas and in almost any weather condition. In this paper an advanced data processing chain able to simultaneously measure a wide range of deformation rates, across four orders of magnitudes, from moderate movements (up to 150 mm/hour) to extremely low displacements (few mm/month), is presented. The use of this processing for long-term monitoring may result in an early detection of slow movements and eventually the setup of remedial before they start to interfere with operations or problems become too difficult or expensive to be managed. The advantages and site experiences are presented along with recent successful studies in several Brazilian iron ore mines with different characteristics, owned by Vale S.A. In the sites radar data have been integrated and compared to displacement measurements acquired by traditional monitoring systems, in order to improve the interpretation of the local slope movements and predict failure mechanisms. This technique is now applied to support long-term monitoring, adding to the traditional systems to provide the necessary reliability, coverage and safety.

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