Discover how 11Foundry and Epoch use geospatial AI and first-mile intelligence to solve timber’s toughest EUDR challenge—delivering accurate, scalable geolocation data across fragmented supply chains.
The European Union Deforestation Regulation (EUDR) requires operators to provide geolocation data corresponding to the plots of land where commodities were produced. In principle, this requirement is straightforward. In the operational reality of timber supply chains, it is often not.
Unlike some other commodities, timber is rarely sourced from centralized production systems with clearly defined boundaries. In regions such as the Southern United States and Western Canada, ninety percent of harvests occur on private land. Three-quarters of that land is owned by non-industrial families and individuals with varied harvesting practices, no obligation, no incentive and often strong reasons not to disclose the exact boundaries of their plots. Even if they disclose, there is limited standardization of geolocation data. Compounding the problem, a single consignment of graded US hardwood lumber in the EU may contain wood sourced from 20,000 to 30,000 individual plots. As a result, the information required for compliance is either not available or not always readily available in a complete or consistent form.
This creates a gap between regulatory expectations and supply chain realities. The challenge is determining how accurate and reliable geolocation data can be developed in environments where it has historically been difficult to obtain.
This paper outlines that challenge and presents a practical, collaborative approach developed by 11Foundry and Epoch.
In many timber supply chains, forest ownership is decentralized and highly distributed. A large majority of harvest activity takes place on privately owned land, much of it held by non-industrial landowners. Harvesting is selective and spread across wide geographic areas rather than concentrated in clearly defined production units.
As timber moves through the supply chain, it is aggregated from many individual harvest events. By the time material reaches an operator placing product on the EU market, it may represent inputs from thousands of distinct locations.
Within this structure, geolocation data presents several challenges. In some cases, precise polygon data is not maintained at the source. In others, it may exist but be difficult to access due to privacy concerns, commercial sensitivities, or the way supply chains are organized. Epoch's approach addresses this directly: by deriving plot-level geolocation data through its geospatial AI tech stack rather than relying solely on landowner disclosure, operators can build defensible compliance datasets without requiring suppliers to expose commercially sensitive information — whether that is precise boundary data, standing timber inventories, or harvest schedules that inform their negotiating position with buyers. This preserves the trust relationships that underpin fragmented supply chains while still meeting EUDR's evidentiary standards. Even where data is available, it is often inconsistent in format, accuracy, or level of detail.
These conditions do not remove the requirement for geolocation under EUDR. They make it more complex. The question becomes how to develop geolocation data that is accurate, reliable, and defensible within these constraints.
In many compliance frameworks, required data is assumed to be directly available from supply chain participants. In timber, this assumption often breaks down.
A more effective approach is to expand beyond data collection to include data development through a combination of inputs and methods. Supplier-provided data remains central. However, it may need to be supplemented, validated, refined, or in some cases reconstructed using additional sources of information.
This includes historical records, spatial context, and independent geospatial observation. The objective is not to bypass what data may be provided directly by upstream partners, but to arrive at accurate and reliable geolocation information through a structured and evidence-based process, even when direct data is incomplete or difficult to obtain.
This expanded approach, combining data collection and data development, is central to making EUDR compliance workable in timber supply chains.
To address this challenge, 11Foundry and Epoch have developed a combined methodology that integrates geospatial analysis with operational due diligence workflows.
This methodology solves cases where harvest sites are not disclosed and reported by producers and where harvest sites are disclosed across varying levels of accuracy or consistency.
For cases where no harvest sites are disclosed, Epoch’s geospatial AI technology stack identifies harvest sites (whether through clear cuts or through thinning) directly across large areas of interest - counties, states or entire sourcing regions, all without any input from producers. This approach enables operators to generate the geolocation data EUDR requires, at scale, without asking producers to disclose commercially sensitive information — whether that is precise boundary data, standing timber inventories, or harvest schedules that inform their negotiating position with buyers. Because this approach only identifies the harvest sites, entire plot boundaries are never shared. Producer privacy is preserved. Anti-trust constraints are respected. And operators get a defensible, evidence-based due diligence system that holds up to regulatory scrutiny.
For cases where harvest sites are disclosed, 11Foundry’s Command Center provides the structure where geolocation data is collected, validated, augmented (if necessary), and evaluated with Epoch’s capabilities, which incorporate multiple authoritative datasets, including JRC, GLAD, TMF, and other global forest monitoring layers, alongside advanced analytical techniques such as Continuous Change Detection and Classification (CCDC). These steps are documented with a complete audit trail as part of the due diligence.
Together, these capabilities support several key processes:
This methodology does not eliminate the need for supplier engagement. It provides a structured way to develop, validate, and contextualize geolocation data when direct collection alone is not sufficient.
This approach is particularly relevant in supply chains characterized by fragmentation and limited data availability. This includes regions with distributed ownership, aggregated sourcing, and developing data systems.
In such contexts, the ability to combine supplier information with independent geospatial analysis can materially improve both the quality of geolocation data and the consistency of due diligence processes.
In supply chains where high-quality geolocation data is already available, these capabilities can still play an important role in validation and verification.
The challenge of geolocation under EUDR in timber supply chains is structural. It reflects the way these supply chains are organized, not simply a lack of technology or data.
Addressing this challenge requires a system-level response. Geolocation data must be developed through a combination of inputs. It must be validated using independent methods. It must be used within a structured and well-documented due diligence process.
The collaboration between 11Foundry and Epoch represents a best-in-class approach to this problem. By integrating geospatial intelligence with operational due diligence systems, it provides a practical framework for developing, validating, and managing geolocation data in line with regulatory expectations.
