Supporting the EU Deforestation Regulation

Deforestation and forest degradation are major contributors to climate change, biodiversity loss, and ecosystem damage. The global demand for commodities like soy, palm oil, beef, coffee, cocoa, and wood drives deforestation, particularly in tropical regions. The challenge is how to monitor, verify, and prevent the import of products linked to deforestation, ensuring compliance with regulations like the EUDR (EU Deforestation Regulation) to protect forests and mitigate environmental harm.

Earth Observation (EO) can significantly aid in combating deforestation by providing near real-time satellite imagery and remote sensing data to monitor forest cover and detect changes. This technology enables the identification of deforestation hotspots, illegal logging, and land-use changes, allowing for timely intervention. EO also supports supply chain transparency by tracing the origins of commodities, ensuring they are sourced from deforestation-free areas. It helps companies produce compliance reports by offering objective and independent verification, enabling them to demonstrate adherence to regulations like the EU Deforestation Regulation (EUDR), ensuring environmental sustainability and forest protection.

Feature image credit: EO4SD-forest

Near Real Time (NRT) Canopy Disturbance

Near Real Time (NRT) Canopy Disturbance identifies new forest canopy disturbances on a high temporal frequency basis. A Near Real Time (NRT) Forest Monitoring System is continuously running and Earth Observation (EO) data is processed as soon as it is available, meaning that the system is activated and updated by each newly acquired EO data set. The type of EO sensors used in the processing chain and their individual repeat pass intervals define the possible frequency of updates to the service.

Image credit: Source EO4SD-Forest

Forest Area and Change

The Forest Area and Change products form the basis for determining gross deforestation rates and for the detection of forest regrowth or replanting. They are used as the benchmark for deforestation/disturbance detection by early warning systems.

Figure: Screenshot of Forest Area and Change. Source: here.

Further sources

Related ESA-funded project

World AgroCommodities (website to be added)

Relevant resources

ESA’s Massive Open Online Courses (MOOCs): a series of online courses which showcase how EO technologies and data applications work, what EO data looks like and how it can have an impact on science and application. These courses are designed for diverse audiences, from policymakers to casual learners.
EO College: A repository platform of digital learning content related to EO remote sensing and related topics. This platform includes ESA’s MOOCs. Coordinated by SAR-EDU, an initiative managed by the Friedrich Schiller University Jena.
Silvacarbon’s e-learning materials: a series of e-learning materials on open tools for Measurement, Reporting and Verification (MRV) developed in collaboration with academia partners and in-kind collaboration from the private sector.
GOFC-GOLD’s REDD+ Training materials: Learning and teaching materials developed by the Global Observation for Forest Cover and Land Dynamics (GOFC-GOLD) and the Forest Carbon Partnership Facility (FCPF).
GFOI’s OpenMRV: An open-source knowledge platform developed by the Global Forest Observation Initiative (GFOI) which provides access to forest-related Monitoring, Reporting and Verification (MRV) support resources (training materials, tool manuals and technical guidance).
SERVIR Global Training Materials: Comprehensive training and workshop materials addressing critical challenges through the use of satellite data and geospatial technology.
Cloud-Based Remote Sensing with Google Earth Engine Book: A free online resource that provides the basics of remote sensing as well as application examples in Google Earth Engine.

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