Credible Data is Crucial for Forest Baselines – Here’s Why

A forest baseline (when built on credible data) is the foundation for consistent deforestation risk assessments, supplier engagement, regulatory compliance (such as the EU Deforestation Regulation – EUDR) and long-term supply chain resilience. Without a trusted reference layer, organisations cannot make confident or defensible sourcing decisions. 

The World Cocoa Foundation’s newly published Cocoa Deforestation Risk Methodology reflects this necessity, setting out best practices for building robust baselines, assessing risk, and considering mitigation measures when deforestation or associated risk is confirmed. Although developed for the cocoa sector, many of the recommendations have wider relevance to other agricultural commodities such as soy, palm oil, coffee, and beyond. For example, the emphasis on integrated baselines, independent accuracy assessment, and transparent decision-making reflects principles that are becoming increasingly important across all forest-risk commodities. Additionally, it acknowledges the need to assess risk not only inside but also around the plot, checking the broader landscape for risks of illegal expansion in adjacent areas over time.

For Satelligence, these recommendations reinforce our long-standing approach to risk assessment and risk mitigation processes, best practices that have been baked into our work from the beginning. A particular example of this is our own forest and ecosystem baseline, the Satelligence Nature Baseline. Rather than relying on a single land cover dataset, we have curated and harmonised over 80 peer-reviewed global, regional, and national datasets to create a single, consistent reference layer that is continuously improved and updated. As industry methodologies continue to evolve, this robust baseline plays an important role as the foundation for credible, defensible sourcing decisions for resilient growth. 

Why are forest baselines becoming an industry best practice?

It used to be the case that organisations needed to choose between competing forest and land cover datasets, with various methodologies, strengths, and limitations. Now, rather than asking which dataset is best, the focus has shifted towards how multiple sources of evidence can be combined to create the most robust foundation for decision-making. 

We see this change reflected across emerging industry guidance; rather than prescribing a single data source, methodologies are increasingly advocating for transparent, documented approaches that evaluate the quality of available datasets, combine complementary and credible data sources, and clearly communicate uncertainty. The goal is not simply to improve mapping accuracy, but to create a consistent reference layer that organisations can confidently use for risk assessments, reporting, and supplier engagement. 

These principles have long underpinned Satelligence’s Nature Baseline. Built using a convergence of evidence approach, it integrates multiple forest and land cover datasets, prioritising sources based on their validated quality and suitability for the local context. 

This approach recognises that no single dataset is perfect. By combining multiple sources of evidence and applying consistent quality assessment, organisations can reduce the limitations of individual datasets and create a more reliable basis for downstream decisions.

From our experience of watching and contributing to the industry’s maturity in Nature Intelligence, we have seen this convergence of evidence become less of a differentiator and more of an expectation.