EGU24-21708, updated on 11 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Due diligence for deforestation-free supply chainswith Sentinel-2 imagery from the Copernicus DataSpace Ecosystem 

Heiko Balzter1, Nezha Acil1,2, Ivan Reading1, Konstantina Bika1, Toby Drakesmith1, Chris McNeill3, Sarah Cheesbrough3, and Justin Byrne3
Heiko Balzter et al.
  • 1University of Leicester, Institute for Environmental Futures, Centre for Landscape and Climate Research, School of Geography, Geology and the Environment, Space Park Leicester, 92 Corporation Road, Leicester, LE4 5SP, UK
  • 2National Centre for Earth Observation, University of Leicester, Space Park Leicester, 92 Corporation Road, Leicester, LE4 5SP, UK
  • 3Satellite Applications Catapult; Electron Building, Fermi Ave, Didcot OX11 0QR, UK

At COP26, the Glasgow Leaders Declaration committed the majority of the world’s nations to
ending deforestation by 2030. On 29 June 2023, the EU Regulation on deforestation-free
products (EU) 2023/1115 entered into force. The main driver of deforestation and forest
degradation is the expansion of agricultural land for the production of commodities like cattle,
wood, cocoa, soy, palm oil, coffee, rubber and derived products. Any trader wishing to sell these
commodities on the EU single market or export from within it, must prove that the products do
not originate from recently deforested land or have contributed to forest degradation.
Satellite imagery provides the means of addressing the implementation of the EU Regulation
on deforestation-free supply chains, and of strengthening forest governance through the
provision of timely information to national forest services. We present the PyEO near-real-time
forest alert system from Sentinel-2, a current operational application to reduce illegal logging in
Kenya, and its potential to support im- and exporters in demonstrating deforestation-free supply
chains developed by the ForestMind project.

The software implementation used the Python for Earth Observation (PyEO) library to
automatically extract information on forest loss from Sentinel-2 satellite imagery. It queries the
Copernicus Data Space Ecosystem for new imagery, downloads the automatically selected
Sentinel-2 images, applies a previously trained random forest machine learning model to detect
forest loss, and generates a multi-layer analyst report.
For the forest law enforcement in Kenya, the latest forest alerts are sifted and prioritised by
the Kenya Forest Service’s Forest Information Centre in Nairobi, and delegated to forest rangers
in the field for investigation. Forest rangers navigate to the field site inside the forest reserve,
accompanied by a local community scout, and report back to head office with their observations
and whether any arrests for illegal logging were made. Since its introduction in Kwale County in
2019, over 2000 forest alerts have been investigated. The dominant cause of the deforestation is
illegal logging, followed by charcoal production.
For the due diligence application, a Forest Analyst can then use the analyst-report and
additional software tools to create company reports suitable for communication to im- and
exporters for monitoring the impact of their supply chains on deforestation and forest


How to cite: Balzter, H., Acil, N., Reading, I., Bika, K., Drakesmith, T., McNeill, C., Cheesbrough, S., and Byrne, J.: Due diligence for deforestation-free supply chainswith Sentinel-2 imagery from the Copernicus DataSpace Ecosystem , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21708,, 2024.