From these measurements they generated a spatially explicit block value (BV) map, translating visual and structural observations into a numeric grade that could guide production decisions in real time. The calculated block values ranged from 1 to 5 across the bench, with a mean of 2.8. Only 6 percent of the mapped blocks reached the highest BV category, while 12 percent fell into the lowest, illustrating how uneven quality distribution is even within a single quarry face.

Because the map is spatially explicit, operators can see where high-value material lies before committing expensive cutting and handling operations. The analysis revealed that the direction of cutting could be aligned with the dominant joint set at the site, a geometric adjustment that improves the recovery of marketable blocks from each extracted volume. When the quarry applied this information to adjust its extraction sequence, the results were measurable.

The section worked under the new plan achieved 14 percent higher marketable block productivity and produced 14 percent less waste volume compared with the quarry-wide average. These figures come from the single case study and reflect one site's geology, so they demonstrate the framework's potential rather than a universal outcome. The authors emphasize that the BV grade map functioned as an internal benchmark.

Because the grade is defined by the stone's own color and structural properties rather than by comparison with external market data, a quarry can adopt the method without a pre-existing baseline, making the approach practical for operations that have never quantified block quality before. The significance of the work lies in filling a long-standing methodological gap. Metallic mining relies on ore grade to drive blending, scheduling, and cut-off decisions, but dimension stone has lacked an equivalent metric, contributing to suboptimal resource utilization and production planning.

A numeric, mappable grade brings the discipline of quantitative resource modeling to an industry that has traditionally depended on qualitative assessment. Beyond productivity, the framework has implications for sustainability. The authors position the approach as a step toward smarter quarrying, in which site-specific geological intelligence, captured through systematic color and fracture mapping, drives more efficient and more sustainable use of dimensional stone resources.

Subject of Research: Quantitative grade determination for dimension stone quarrying using color and fracture mapping

Article Title: Grade determination from systematic color and fracture mapping enables smart quarrying of dimension stone

Article References: Yarahmadi, R., Ranjbar, G., & Sarikhani Khorrami, M. (2026). Grade determination from systematic color and fracture mapping enables smart quarrying of dimension stone. Scientific Reports. https://doi.org/10.1038/s41598-026-77315-w

Image Credits: AI Generated

DOI: 10.1038/s41598-026-77315-w

Keywords: dimension stone, quarrying, block value, color mapping, fracture mapping, discontinuity analysis, marble, block recovery, waste reduction, grade determination, sustainable mining, Scientific Reports