Assessing the use of AI and remote sensing for European Union Deforestation Regulation (EUDR) supply chain tracing
Date
2026
Authors
Holmes, Chris
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Journal ISSN
Volume Title
Publisher
University of Victoria
Abstract
Tropical deforestation remains a major source of global emissions, with a substantial share associated with international commodity supply chains. In response, policymakers are turning to evidence-based governance by deploying spatial monitoring to regulate forest-commodity impacts, exemplified by the European Union Deforestation Regulation (EUDR), which requires proof that imports such as soy, palm oil, cocoa, and timber are deforestation-free. As a result, a growing number of private tracing firms have developed geospatial platforms that use satellite imagery, machine learning, and farm-level mapping to support due diligence and compliance. However, there remains limited research on how these tracing systems actually operate, what data they rely on, and what broader implications they may have for environmental sustainability and equity on the ground. This research addresses that gap by asking how EUDR tracing companies gather and analyze supply chain data, and what implications this has for environmental sustainability and equity in producer countries. The research draws on semi-structured qualitative interviews with both academic experts and private industry experts involved in supply-chain tracing.
Description
Keywords
Deforestation, environmental governance, remote sensing, supply chain tracing, Jamie Cassels Undergraduate Research Awards (JCURA)