Introduction
The European Union Deforestation Regulation (EUDR) mandates that companies ensure their products are not linked to deforestation after December 31, 2020. Orbify’s EUDR compliance assessment provides a structured, data-driven approach to evaluating whether a plot of land adheres to these regulations.
This guide explains how Orbify determines compliance, what influences the results, and how users can interpret and act on the insights provided.
1. How Orbify Assesses EUDR Compliance
Orbify’s compliance algorithm follows a systematic, multi-step methodology to analyze project plots based on satellite data, land classification models, and risk indicators.
Step 1: Coordinate Precision Assessment
Orbify begins by ensuring that project plot boundaries meet the coordinate precision requirements of the EUDR regulation.
This establishes a baseline for accurate compliance analysis.
Step 2: Ecoregion-Based Forest Typing
Depending on the ecoregion of a given plot, the algorithm determines the expected forest type.
This step tailors the analysis to the specific vegetation and forest characteristics of the region.
Step 3: Data Fusion with Consensus Analysis
The system integrates multiple datasets to cross-check forest presence at the EUDR cutoff date (December 2020). Key datasets include:
EC JRC Forest Cover
WRI DataLab Tropical Tree Cover Extent
Hansen Global Forest Change
Sentinel-2 Land Use Land Cover (LULC) Data
Commodity plantation databases (soy, rubber, timber, etc.)
Using a voting mechanism, these datasets confirm the presence or absence of forests, ensuring high accuracy.
Step 4: Filtering of Non-Eligible Areas
The algorithm applies additional filters to exclude areas that should not be classified as forests, such as:
Planted forests
Agricultural commodity plantations (e.g., soybean, rubber, timber plots)
This ensures the system focuses only on natural forests for compliance assessments.
Step 5: Deforestation Verification
If a plot was identified as forested in December 2020, the system checks for forest loss since that date.
This verification uses Hansen Global Forest Change data and other remote sensing tools to detect deforestation.
If deforestation is detected after December 2020, the plot is flagged as likely non-compliant with EUDR.
2. Understanding Compliance Results
Based on this structured analysis, Orbify assigns one of the following compliance statuses:
Compliance Status | Meaning |
⚠️ Low canopy cover or scattered trees detected | Manual inspection recommended due to uncertain forest classification. Users should analyze additional data layers for verification. |
✅ No forest present in 2020 | The plot is likely compliant with EUDR regulations as it was not forested at the cutoff date. |
❌ Forest removal since 2020 | The plot is likely non-compliant, as deforestation has been detected after December 2020. |
✅ Stable forest detected | The plot is likely compliant, as no forest loss has been observed since 2020. |
3. Key Considerations & Limitations
A. Resolution & Conservative Screening Approach
Different datasets used for compliance assessments range in spatial resolution from 5m to 30m.
Orbify aligns project shapes to the resolution of these datasets for accuracy.
The system applies a conservative screening approach, meaning that even small deforestation pixels influence the final result.
If flagged as non-compliant, users should verify results using high-resolution optical imagery.
B. Managing False Positives
Orbify's system is intentionally cautious, flagging potential non-compliance when uncertainty exists.
This approach ensures even subtle deforestation indicators are reviewed, reducing the risk of overlooking violations.
C. Commodity Plots & Plantations
False negatives can occur when a plot is located within planted forests or commodity plots.
If a result seems inaccurate, users can contact Orbify Support to refine the analysis.
Orbify continuously updates its commodity plot database to improve accuracy.
D. Forest Map Quality Screening
This feature complements auto-compliance screening by improving:
Validation of forest benchmark maps
Accuracy of forest loss detection
Users are encouraged to cross-check with this tool for a more thorough compliance evaluation.
4. How to Examine Graphs, Tables, and Individual Data Points
To gain deeper insights and validate results, users should analyze the graphs, tables, and individual data points presented in the compliance assessment:
Graphs: Provide visual trends over time, showing tree cover loss, deforestation events, and NDVI-based vegetation indices.
Tables: Present numerical breakdowns, including land use statistics, percentage of tree cover change, and classification scores from different datasets.
Individual Data Points: Users can click on specific points to review historical satellite imagery, ensuring that flagged areas align with deforestation trends.
For a more thorough validation, consider comparing multiple data sources and cross-referencing with official documentation or third-party verification tools.
5. What to Do Next?
If your plot is flagged as non-compliant or requires manual inspection, follow these steps:
Check the detailed data layers within Orbify, including historical land cover and satellite imagery.
Compare against official documentation for the land in question.
Use high-resolution optical imagery to verify deforestation claims.
Analyze graphs, tables, and data points to identify discrepancies or patterns.
Contact Orbify Support if you suspect a false positive or require further assistance.
Conclusion
Orbify’s EUDR compliance assessment provides a robust, scientifically grounded method for evaluating forest cover changes and deforestation risks. While the system offers highly accurate insights, manual verification remains essential in ambiguous cases.
By leveraging Orbify’s data fusion, conservative screening approach, and advanced algorithms, businesses can confidently navigate EUDR regulations and ensure their supply chains remain deforestation-free.
Need Help? If you have any questions or require further verification, feel free to contact Orbify Support for assistance.