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NEWS
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August 12, 2024
Written by
Caroline Busse
Copernicus Sentinel data is being used by chocolate producers to ensure that the cacao they source from tropical regions is not contributing to deforestation. In 2023, the new EU Regulation on Deforestation-free products (EUDR) came into force and means that any operator or trader who places certain commodities on the EU market, must be able to prove that the products do not originate from recently deforested land or have contributed to forest degradation.
Original Beans, a Dutch chocolate manufacturer, is using Nadar's EUDR service based on Sentinel-2 data in order to ensure and demonstrate that the cacao they source from Peru is not contributing to deforestation. Original Beans sources cacao from all around the world, including Peru, Ecuador, Columbia, Bolivia, Mexico, the Dominican Republic, the Democratic Republic of the Congo, and Tanzania.
In Peru, they work with APPCACAO, the national trade association that represents Peruvian cacao producers on national and international policy issues that are important to the cacao sector. APPCACAO facilitates trade by providing information about cacao offerings on behalf of its partner cooperatives. They act as a connector, promoting Peruvian cacao and helping interested buyers find the best cacao in Peru.
Nadar is a German-based SME who specialise in EO-enabled forest monitoring services. Among their services they provide carbon sequestration Monitoring, Reporting, and Verification (MRV) solutions. They have developed an end-to-end software solution, based on Sentinel-2 derived time series indexes that ensures compliance with the EUDR.
Copernicus Sentinel-2 carries an innovative wide swath high-resolution multispectral imager with 13 spectral bands. The combination of high resolution, novel spectral capabilities, a swath width of 290 km and frequent revisit times provides unprecedented views of Earth. Sentinel-2 images can be used to determine various plant indices such as leaf area chlorophyll and water content providing information useful for agricultural and forestry practices and for helping manage food security. Sentinel-2 also provides information on pollution in lakes and coastal waters. Images of floods, volcanic eruptions and landslides contribute to disaster mapping and help humanitarian relief efforts.
Nadar is a remote sensing company who has developed a solution which aims to support traders and importers of various products under the EUDR, including cocoa, by mapping their farms, monitoring deforestation with confidence, and creating the required due diligence documents.
Nadar use Sentinel-2 data, in conjunction with other commercial data sources to map areas of commodity cultivation (currently cacao, coffee and rubber) and then assesses whether this activity is contributing to deforestation/degradation. There are several steps to this process.
First, supplier information is gathered and farm plots geolocated. Using a mobile application, the user can then outline the plot boundaries. Once completed, Nadar can perform deforestation checks using Sentinel data with the solution being able to differentiate between natural forest and plantations using AI and time series analysis. A risk assessment is then conducted based on the geospatial analysis and country-level risk indicators. Finally, a due diligence statement is produced which can automatically interface with the EUDR Information System.
This is useful because before introducing a commodity into the market, traders must make available to the competent authorities a corresponding due diligence statement via a register that has been set up by the European Commission. Authorities explicitly promote the use of geographic information as part of these due diligence checks, including the use of remote sensing i.e., Copernicus and/or other sources and GNSS coordinates to locate specific forest plots i.e., via Galileo and/or other sources.
Nadar utilises a Machine Learning approach to detect deforestation with Sentinel data and time series analysis. Time series analysis is widely used for identifying abrupt changes by analysing repeated data from specific locations (pixels) where the forest may have experienced disturbances at certain times. They rely on variables derived from the raw EO data, including vegetation indices such as the Normalized Difference Vegetation Index (NDVI), and the Enhanced Vegetation Index (EVI).
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Caroline is an experienced data scientist with a management degree from TU Munich and a degree in earth observation from the University of Würzburg, which is co-chaired by the German Aerospace Center (DLR). She has worked as a data scientist in the areas of nature conservation and land use change monitoring at WWF, the German Centre for Integrative Biodiversity Research (iDiv), and at tech companies such as Celonis and Deloitte.