Abstract:
Monitoring and estimating solid mine waste produced during mining operations at a spatial–temporal scale plays a fundamental
role in waste management and mitigation of environmental impacts. Iron ore mining and processing results in waste
production that may cause environmental degradation, therefore, the need to estimate their volumes and extents. This research
aims at mapping and estimating the areal extents and the volumes of solid mine waste produced during iron ore mining and
processing. Contours were generated from control points with X, Y, Z information and interpolated to create a Triangular
Irregular Network (TIN), which was rasterized to create a 3D Digital Elevation Model (DEM) that was used in volume estimation.
Maximum-Likelihood Classification method (MLC) was used for classification at an accuracy of 74% to estimate
the areal extents of the solid mine wastes, with a Kappa Coefficient of 0.65. Solid mine waste approximately covered an area
of 591,100 m2
and a volume of 2694,670.55 Metric Tonnes. This research presents a fast and accurate method of mapping
and estimating the areal extents and volume of solid waste dumped during mining and processing operations.
