1174 support a shift in how nature is understood and managed within the mining sector. By embedding environmental data within operational and stakeholder-facing workflows, such approaches offer potential to improve transparency, support adaptive management, and strengthen trust. Future research and application should focus on refining indicators, strengthening integration with decision-making processes, and evaluating long-term outcomes across a broader range of mining contexts. 9. CONCLUSIONS AND IMPLICATIONS FOR INDUSTRY This paper has presented an applied framework for integrating multi-dimensional data into mining operations through a digital reality approach to environmental monitoring with Green Cubes. The methodology was demonstrated through two real-world implementations in the extraction industry, showing that integrated, continuous environmental monitoring can be deployed in both post-operational and restoration-focused mining contexts. The results indicate that combining environmental data within a single pane of glass can improve visibility of ecological conditions, support restoration planning, and enhance stakeholder engagement. The implementations at Vale and Samarco illustrate how environmental monitoring can evolve from fragmented, compliance-driven assessments toward a more integrated and operationally relevant practice. By establishing spatially explicit baselines and enabling continuous tracking of environmental change, the approach supports adaptive management and provides a more robust basis for reporting biodiversity impacts and restoration outcomes. Improved visibility of environmental conditions also contributes to clearer engagement with regulators, communities, and internal decision-makers. For the mining industry, these findings highlight the potential value of embedding environmental monitoring within operational workflows rather than treating it as a parallel or external process. Integrated digital environmental management can support earlier consideration of restoration and closure, reduce uncertainty, and strengthen trust by making environmental performance more transparent and accessible. The phased deployment model demonstrated in this paper further suggests a practical pathway for adoption that aligns with operational realities and regulatory processes. At the same time, successful implementation requires collaboration across disciplines, including environmental specialists, operational teams, and technology providers. Clear governance of data, careful selection of indicators, and ongoing field validation remain essential to ensure that digital representations accurately reflect ecological conditions. As regulatory and disclosure expectations continue to evolve, alignment with emerging biodiversity reporting frameworks will be critical to maximising the value of integrated monitoring approaches. In conclusion, the approach presented in this paper demonstrates how technology-enabled environmental management can support more responsible, efficient, and transparent mining practices. By providing consistent, scalable, and decision-relevant environmental information, integrated digital monitoring, AI processing and easily accessible visualization, has the potential to play a meaningful role in advancing trust, enabling transformation, and supporting sustainable outcomes across the mining lifecycle. Future applications should focus on expanding implementation across diverse mining contexts and evaluating long-term environmental and social outcomes to further inform industry practice. REFERENCES Sonter, L. J., Ali, S. H., & Watson, J. E. M. (2020). Mining and biodiversity: Key issues and research needs in conservation science. Proceedings of the National Academy of Sciences, 117(8), 3778–3785. Available at: https://gecamin.com/planningforclosure/authors.php
RkJQdWJsaXNoZXIy MTM0Mzk2