In surface mining, rockfall can seriously threaten the safety of personnel located at the base of highwalls and cause serious damage to equipment and machinery. Close-range photogrammetry for the continuous monitoring of rock surfaces represents a valid tool to efficiently assess the potential rockfall hazard and estimate the risk in the affected areas. This work presents an autonomous terrestrial stereo-pair photogrammetric monitoring system developed to observe volumes falling from sub-vertical rock faces located in surface mining environments. The system has the versatility for rapid installation and quick relocation in areas often constrained by accessibility and safety issues and it has the robustness to tolerate the rough environmental conditions typical of mining operations. It allows the collection of synchronised images at different periods with high-sensitivity digital single-lens reflex cameras, producing accurate digital surface models (DSM) of the rock face. Comparisons between successive DSMs can detect detachments and surface movements during defined observation periods. Detailed analysis of the changes in the rock surface, volumes and frequency of the rocks dislodging from the sub-vertical rock surfaces can provide accurate information on event magnitude and return period at very reasonable cost and, therefore, can generate the necessary data for a detailed inventory of the rockfall spatial-temporal occurrence and magnitude. The system was first validated in a trial site, and then applied on a mine site located in NSW (Australia). Results were analysed in terms of multi-temporal data acquired over a period of seven weeks. The excellent detail of the data allowed trends in rockfall event to be correlated to lithology and rainfall events, demonstrating the capability of the system to generate useful data that would otherwise require extended periods of direct observation.
Theoretical Basis for Multiple Criteria Analysis of Variants and Selection of the Most Effective Technological Scheme for Hard Rock Surface Mining