SmallMinesDS: A Multimodal Dataset for Mapping Artisanal and Small-Scale Gold Mines

Abstract

The increasing demand for gold, coupled with persistently high market prices over the past decade, has driven a significant rise in small-scale gold production. The expansion of unregularized small-scale gold mines fuels environmental degradation and poses a risk to miners and mining communities. To promote sustainable mining practices, support reclamation initiatives, and pave the way for understudying the impacts of mining on human and environmental resources, we present SmallMinesDS, a benchmark dataset derived from multisensor satellite imagery covering five districts in southwestern Ghana in two time periods. SmallMinesDS provides precise reference data for artisanal mining sites, enabling the development of machine learning models for timely, large-scale, and cost-effective monitoring. Notably, foundation models (FMs) fine-tuned on SmallMinesDS achieve up to 75% intersection over union while maintaining a strong balance between minimizing false positives and negatives.