264 to reduce reliance on single-method assessments, supporting a more comprehensive baseline and AI monitoring capability. The collected datasets are integrated within a digital reality framework representing the physical environment of the mining site and its surrounding ecosystems. Environmental conditions are visualised and analysed in three dimensions and over time, with metrics organised across physical volume, structural complexity, and biodiversity indication. This structure supports consistent comparison of environmental conditions across locations and monitoring periods. A baseline assessment is established at the outset of application, integrating site knowledge, existing scientific data, and captured measurements. This baseline serves as a reference for tracking environmental change and progress over time, with periodic updates enabling trend identification and targeted intervention where restoration outcomes are not progressing as expected. In this way, environmental change is linked directly to operational and restoration decisions to support adaptive management. A digital platform consolidates environmental metrics and provides tools for visualisation, change detection, and AI Large Language Model (LLM) reporting. Outputs include spatial visualisations, trend analyses, and structured reports that can be aligned with regulatory and sustainability reporting requirements. By centralising environmental data within a single interface, the platform supports consistent communication with internal decision-makers, regulators, and other stakeholders. Overall, the methodology emphasises practical deployment, integration with existing operational systems, and scalability across different mining contexts. Rather than replacing established environmental practices, the approach is designed to complement them by improving data continuity, visibility, and usability throughout the mining lifecycle. 6. DESCRIPTION OF TECHNOLOGIES / PROCESSES / PARTNERSHIPS 6.1 Green Cubes: Integrated Technologies, Processes, and Partnerships Green Cubes (Digital Reality, n.d.), the digital reality approach, provides spatially explicit indications of forest volume, structural complexity, and biodiversity indication across terrestrial areas at scale. The approach is developed in collaboration with engineers and leading scientists, with the objective of strengthening conservation outcomes while continuously refining the underlying methodology. The Green Cubes methodology integrates technologies ranging from earth observation to subsurface measurement, enabling the creation of a comprehensive digital representation of forested environments. These data streams are merged and visualized within the Green Cubes platform to support monitoring, analysis, and internal and external engagement.
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