A Digital Twin and Procedural-DAO Architecture for EUDR-Specific Deforestation Monitoring under Evolving Regulatory Requirements

Abstract

The EU Deforestation Regulation (EUDR), Regulation (EU) 2023/1115, requires operators and traders placing cattle, cocoa, coffee, palm oil, soya, wood, rubber, charcoal and their derived products on the EU market to demonstrate that the underlying commodities are deforestation-free after 31 December 2020, are legally produced, and are covered by a due diligence statement. While deforestation detection is often treated as the technically dominant requirement, EUDR compliance is broader: it also requires traceability across supply chains, provenance of production, country-specific legal context, and auditable due diligence processes. Translating these obligations into an inspectable, reproducible, software-supported workflow raises three coupled problems: (i) the regulation itself is a moving artefact whose definitions, country risk classifications and implementing acts evolve; (ii) the geospatial evidence used to satisfy Article 3(a) depends on upstream datasets-primarily the Hansen Global Forest Change product-whose versions, tile schemes and methodological conventions also change; and (iii) the resulting compliance interpretations cannot be ethically delegated to a fully autonomous agent because they affect market access, livelihoods and the legal exposure of operators. This paper describes an architecture that addresses these problems jointly through a closed feedback loop linking regulation, data dependencies, implementation, validation, and governance. We separate authoritative deterministic generation of evidence from a public, non-authoritative Digital Twin portal that exposes system state, dependencies, and example outputs for inspection. A procedural Decentralized Autonomous Organization (DAO)implemented in this work as a file-grounded YAML proposal workflow, but compatible with optional blockchain anchoring of evidence digests and proposal records-closes the governance loop between stakeholders, developers, and evolving regulatory interpretation. The procedural design is deliberate: as we discuss below, the kind of DAO appropriate for governing truth claims about the physical world differs in object, voting subject and failure mode from the protocol-governance DAOs commonly associated with the term, and the choice to run the governance layer off-chain reflects that difference rather than a rejection of distributed-ledger technology as such. An LLM-based Digital Twin Engineer (DTE) agent supports inspection and proposal drafting under strict grounding rules, but never executes code or makes compliance determinations. We describe the multi-repository implementation, the deterministic evidence bundle contract, the public/private trust-zone separation that protects per-operator plot data while allowing example reports to be inspected publicly, and the regulation-as-dependency feedback loop that forces reruns of impacted methods when upstream artefacts change. Although the current implementation focuses primarily on geospatial deforestation evidence, the proposed pipeline is intended as a practical starting point for progressive enrichment as new forms of land intelligence, supply-chain transparency, legal provenance data, and business-network evidence become available. We argue that this design is a generalisable pattern for compliance domains in which regulatory requirements evolve over time and implementations must remain inspectable, reproducible, extensible, and corrigible by humans.