The Hidden Risks of Satellite Deforestation Alerts: How to Mitigate False Positives for EUDR Compliance?
- Gusi Ayu Putri Chandrika Sari
- 1 day ago
- 5 min read
Updated: 13 hours ago
Editor’s note:
As forest monitoring tools become central to regulatory compliance, understanding their limitations is critical. This article explores the growing risks of false positives in satellite-based deforestation alerts and the critical role ofground-level data instrengtheingn traceability efforts under the EUDR. featuring insights from Anggoro Wicaksono, Rubber Project Lead at KOLTIVA and Roland Sinulingga, Environmental Lead at KOLTIVA, the piece highlights how combining satellite intelligence with field verification is key to building credible, deforestation-free supply chains.
Executive Summaries:
Satellite maps are essential, under the EUDR, agribusinesses must prove their supply chains are deforestation-free using geolocation and risk assessments, but there is a possibility of error or misinterpretation, often referred to as false positives or false negatives.
Why do false positives/negatives happen? Forest maps, such as those developed by the the Joint Research Centre (JRC), are designed to prioritize caution—often triggering false positives—and how this shifts verification responsibility to companies.
Field data is critical to validate or dismiss satellite alerts. Koltiva tackles this challenge by combining satellite alerts with field verification through its KoltiTrace MIS platform and KoltiSkills teams—using farmer profiling, geolocation mapping, and deforestation assessments to validate or dismiss alerts.
The EU Deforestation-Free Products Regulation (EUDR) requires agribusinesses to prove that their products are deforestation-free using geolocation and risk assessments. As a result, satellite-based maps have become essential tools in this process. But there's another challenge: correctly interpreting satellite deforestation alerts—particularly those that turn out to be false positives.
In remote sensing, the accuracy of maps is evaluated by comparing mapped changes to “truth data”—ground-verified or independently interpreted satellite imagery. This truth data must be assessed independently, without viewing the map being tested, to ensure objective validation. Overall accuracy measures how often the map matches the truth data, but it can be misleading. When stable land cover (e.g., undisturbed forest) dominates the landscape, even inaccurate change detections may be statistically overshadowed. That’s why analyzing false positives (commission errors) and false negatives (omission errors) gives a more meaningful view of data reliability (Global Forest Maps, 2015).
A false positive in deforestation mapping occurs when an area is wrongly flagged as deforested. These errors can trigger costly field investigations, delay shipments, or even lead to non-compliance claims—despite no actual forest loss.
Our KoltiTrace MIS Land Use Tracker feature allows companies to cross-reference deforestation alerts using multiple datasets, including the Joint Research Centre (JRC) V2, Global Forest Watch (GFW), and the Science Based Targets Network (SBTN). Since no single map is 100% accurate, we empower users to select the dataset most relevant to their geography, land use type or commodity, and reporting needs.
One of the maps available on the KoltiTrace MIS Land Use Tracker is JRC’s Global Forest Cover Map V2 (2020 version). Among the two available versions of the map, KoltiTrace MIS has adopted Version 2 for its improved performance in supporting users to make more informed, evidence-based decisions when assessing potential deforestation in their supply chains. This version shows:
91% overall accuracy
8% omission error (missed forest areas)
18% commission error (non-forest areas misclassified as forest)
In our latest webinar Beyond Traceability Talks Vol. 3, René Colditz, Scientific Project Officer (Project Lead) from the European Commission’s Joint Research Centre (JRC)—which developed the study Accuracy Assessment of the Global Forest Cover Map for the Year 2020: Assessment Protocol and Analysis—explained that the JRC map slightly overestimates forest areas by about 12% compared to FAO’s global estimates.
He further explained the rationale behind this over-flagging approach:
“Global Forest Cover Map V2 system currently tends to produce more false positives than false negatives, and this is intentional. Why? Because from a regulatory perspective, it’s safer to flag a potential risk than to miss an area that may actually be non-compliant. If a deforestation risk goes undetected and a company proceeds without further checks, the risk of EUDR non-compliance is higher. Our (JRC) goal is to serve as an initial filter—to highlight areas where more investigation is warranted. Then, it’s up to the operator to dig deeper and determine whether the alert reflects actual deforestation.”
While this conservative mapping approach supports regulatory caution, it also increases the risk of over-flagging. This raises a critical question for companies: How can they confidently distinguish real deforestation from mapping errors?
Why Satellite Deforestation Alerts Alone Aren’t Enough for EUDR Compliance
Satellite imagery remains a vital resource for prioritizing compliance checks. It helps companies identify high-risk areas and reduces reliance on expensive high-resolution imagery. However, maps have limitations.
Under the EUDR, “forest” is defined by strict parameters:
Tree height of at least 5 meters
Canopy cover of 10% or more
Minimum area of 0.5 hectares
Excludes agricultural tree plantations (e.g., oil palm, rubber)
Maps alone often struggle to capture this nuance, especially in regions with mixed agroforestry systems, regrowth areas, or smallholder mosaic landscapes.
The Path Forward: Pairing Satellite Insight with Risk Mitigation by KoltiSkills
Our boots-on-the-ground extension services (KoltiSkills) help companies mitigate risks where they matter most—the first mile of their supply chains. By combining satellite insights with verified field data, we provide end-to-end traceability that meets the demands of global regulations like EUDR.
When satellite alerts indicate potential deforestation, our field teams provide on-site verification to validate or dismiss those signals:
Ground Verification
Field teams visit the location of the alert to assess whether deforestation actually occurred. This step helps avoid false positives that could unjustly exclude compliant farmers.
Comprehensive Deforestation Assessment
We document a full picture of the land and its history, including:
Observation and documentation of the current state
Growth stage, signs of replanting
Historical timeline of land clearing and land-use changes
Presence of forest
Land tenure and land use history
Land burning history
Deforestation Status Verification
We determine whether the deforestation alert is valid and, if so, whether it is linked to a specific commodity or caused by other factors (e.g., infrastructure, natural disturbance).
“A satellite alert should mark the beginning of a deeper investigation—not serve as the final verdict. On-the-ground validation turns initial risk signals into informed, evidence-based decisions. Without field checks, companies risk excluding compliant farmers based on assumptions, not reality. That’s exactly what we do at Koltiva: we combine satellite mapping with boots-on-the-ground ground-truthing to deliver a complete verification process for EUDR compliance,” said Anggoro Wicaksono, our Project Lead.
This integrated field data helps confirm or refute deforestation alerts—ensuring that supply chain actors don’t wrongly exclude compliant farmers or overlook actual risks. While satellite maps are essential for early detection, true EUDR-aligned traceability requires a full approach: combining digital insight with human intelligence.
Need help validating deforestation alerts or building EUDR-compliant supply chains? Talk to our EUDR experts today.
Author: Gusi Ayu Putri Chandrika Sari, Sustainable Communications Specialist
Subject Matter Expert: Anggoro Wicaksono, Rubber Project Lead & Roland Sinulingga, Environmental Lead
About the Expert:
Anggoro Wicaksono is the Rubber Project Lead at Koltiva, where he champions traceability for inclusive and deforestation-free supply chains. He leads initiatives that integrate satellite intelligence with on-the-ground field verification to meet stringent regulatory standards, including the EU Deforestation-Free Regulation (EUDR). A graduate of the University of Muhammadiyah Malang and Politechnika Lubelska, Anggoro brings a strong foundation in sustainable agriculture and supply chain risk assessment, working closely with smallholder farmers to build resilient, compliant commodity networks.
Roland Sinulingga is a seasoned geo-information professional with over 13 years of experience in Geographic Information Systems (GIS) and remote sensing. His work spans across natural resource management, HCV/HCS assessments, plantation monitoring, spatial planning, and sustainability development. Roland has led and supported technical projects across Indonesia—from Aceh to Papua—as well as in Japan and the Netherlands. With deep expertise in spatial databases and earth observation, he brings a strong commitment to applying geospatial intelligence for sustainable land use and environmental protection.
Resources:
Global Forest Watch. (2015). How accurate is accurate enough? Examining the GLAD Global Tree Cover Change data (Part 1). https://www.globalforestwatch.org/blog/data-and-tools/how-accurate-is-accurate-enough-examining-the-glad-global-tree-cover-change-data-part-1/
Colditz, R., Verhegghen, A., Carboni, S., Bourgoin, C., Duerauer, M., Mansuy, N., De Marzo, T., Beuchle, R., Janouskova, K., Armada Bras, T., Desclée, B., Orlowski, K., Mutendeudzi, M., Ameztoy Aramendi, I., Fritz, S., Lesiv, M., Oom, D., Carreiras, J., San-Miguel, J., Herold, M., ... Achard, F. (2025). Accuracy assessment of the global forest cover map for the year 2020: Assessment protocol and analysis (JRC Technical Report No. JRC141231). Publications Office of the European Union. https://data.europa.eu/doi/10.2760/7632707
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