MINE WASTE VOLUME CALCULATIONS FROM REMOTE SENSING: EVALUATION OF GEOMETRIC TECHNIQUES, AND THE DEVELOPMENT AND APPLICATION OF A NEW GEOPROCESSING TOOL

There are thousands of mine waste features in the United States. On one hand, these may pose environmental hazards. On the other hand, reprocessing some mine waste features could lead to recovery of critical minerals and other commodities that are needed by 21st century societies. The U.S. Geological Survey’s mineral deposit database project (USMIN), in collaboration with State Geological Surveys, is compiling an inventory of non-fuel mine waste features in the United States, as part of the Earth Mapping Resources Initiative (Earth MRI). The inventory’s assessment of resources that meet societal needs will aid in prioritization of environmental hazard remediation while strengthening supply chains of critical minerals.

Estimating the endowment of commodities in mine waste features requires information such as volume, tonnage, and grade. Volume can be approximated through geographic information systems (GIS) without field-based measurements, but there is not a consensus on a best method. The national scale of our database makes field measurements of each feature impractical, so our approach was to assess five pre-established GIS-based volume calculation methods that utilize varying geometric assumptions: surface volume, cylinder, cut fill, cone, and linear regression. Local topography impacts the method of waste storage and thus the geometry of the feature. We categorized features into four types: piles, abutments, flat ponds, and valley fills. To evaluate each method’s accuracy, we compared volume calculations for 150 mine waste features to previously published volume estimates. This comparison showed the linear regression method was the most consistent and accurate across all four types of waste features.

We built a geoprocessing tool in ESRI ArcGIS Pro to automate calculating the volume of all features in the database using the linear regression method. This tool uses areal extents and digital elevation models to calculate the volume of mine waste features by assuming that the thickness of waste at every point within the feature is a function of its distance from the perimeter. The geoprocessing tool will enable the USMIN team and collaborators to determine a preliminary estimate of the distribution and volumes of mine waste at a national scale, allowing for the first large-scale inventory of internally consistent data for mine waste volumes within the United States.