EUDR Deforestation Thumbnail Interpretation Guide

This guide helps you understand and interpret the deforestation check thumbnails generated by the SCo2-API. These visualizations are essential tools for assessing EUDR compliance and understanding deforestation risks in your supply chain.

Overview

Deforestation check thumbnails provide visual evidence of forest change detection, commodity presence, and natural forest baselines. They come in two main types:

1. Plot-level thumbnails: Show deforestation detection for individual farm plots or parcels
2. Supply-shed level thumbnails: Show aggregated deforestation patterns across larger statistical regions (administrative units, watersheds, etc.)

Both types use the same color-coding system to help you quickly identify compliance risks and understand the relationship between deforestation, commodity production, and natural forest areas.

Understanding the Three-Panel Layout

Each thumbnail consists of three vertically stacked panels:

1. Top Panel (Before): Shows the satellite imagery from the start of the monitoring period (typically the EUDR cut-off date of December 31, 2020)
2. Middle Panel (After): Shows the satellite imagery from the end of the monitoring period, allowing you to visually compare changes over time
3. Bottom Panel (Change Detection Overlay): Shows the color-coded overlay combining deforestation alerts, commodity presence, and natural forest baselines

The imagery in the top and middle panels is always taken from the same time of year (when possible) to ensure seasonal comparability, making actual changes more visually apparent.

Primary Color Categories

The bottom panel uses three primary colors, each representing a different data layer. Understanding what each color represents is crucial for interpreting the results.

Red: Canopy Cover Change Detection

What it shows: All detected deforestation and canopy cover loss events within the monitoring period.

Data sources combined: - GFW-GLAD Annual Forest Loss: Global Forest Watch's annual forest loss dataset (30m resolution) - JRC-TMF Deforestation Alerts: Joint Research Centre's Tropical Moist Forest annual deforestation layer (30m resolution) - Epoch's Dynamic World-CCDC: Epoch's high-resolution (10m) change detection using Continuous Change Detection and Classification algorithm applied to Sentinel-2 satellite imagery

What this means: Red pixels indicate areas where forest cover has been lost or significantly degraded. These detections are filtered to only show changes within natural forest areas (excluding water bodies and built-up areas).

Interpretation: Red areas represent potential non-compliance with EUDR regulations, as they indicate deforestation that occurred after the December 31, 2020 cut-off date.

Placeholder: Figure showing red deforestation detection layer

Blue: Commodity Layer

What it shows: The presence of your target commodity (the specific crop type associated with your collection).

Data sources: Commodity-specific probability models from the Forest Data Partnership, including: - Palm oil plantations - Cocoa plantations - Rubber plantations - Cattle grazing areas - Soy cultivation - Timber production areas - Coffee plantations - Sugar cane fields

When it appears: The blue commodity layer is only shown when: - A collection_hash is provided in the API request - Commodity information is available from the collection metadata - The specific commodity type can be identified

What this means: Blue pixels show where your target commodity is detected within the plot or region. This helps you understand whether deforestation is related to your specific supply chain.

Interpretation: When blue overlaps with red (creating magenta), it indicates deforestation is occurring in areas where your commodity is present—this is the most critical scenario for EUDR compliance.

Placeholder: Figure showing blue commodity detection layer

Green: Natural Forest Baseline

What it shows: The extent of natural forest as it existed in the reference year 2020 (prior to the EUDR cut-off date).

Data sources: - JRC-GFC2020 Forest Mask: Joint Research Centre's Global Forest Cover 2020 dataset, which serves as the reference for tree cover definition - JRC-TMF2020 Forest Mask: Tropical Moist Forest extent from 2020 (available in humid tropics) - Google DeepMind Natural Forests of the World 2020: Global 10-meter resolution probabilistic map of natural forest - Forest Data Partnership Forest Persistence: Identifies natural (non-commodity) forest stands

What this means: Green pixels represent areas that were classified as natural forest in 2020. This baseline is crucial for EUDR compliance, as the regulation specifically targets deforestation of natural forests.

Interpretation: Green areas show the natural forest extent that should be protected. When deforestation (red) overlaps with natural forest (green), creating yellow, it indicates deforestation of natural forest—a key compliance concern.

Placeholder: Figure showing green natural forest baseline layer

Color Combinations and Their Meanings

When the three primary layers overlap, they blend to create secondary colors. Each combination tells a specific story about the relationship between deforestation, commodity production, and natural forest.

Yellow (Red + Green): Deforestation in Natural Forest (Potentially Compliant)

What it means: Forest change detection overlapping with natural forest baseline.

Interpretation: This indicates deforestation or forest degradation occurring in areas that were natural forest in 2020. This combination may represent deforestation that is still compliant with EUDR if: - The deforestation occurred before December 31, 2020 (the EUDR cut-off date) - The deforestation is not related to commodity production (no blue/commodity layer present) - The area is not being used for the target commodity in your supply chain

Key point: Yellow indicates deforestation of natural forest, but without the blue commodity layer, it suggests the deforestation may not be directly linked to your commodity sourcing. This makes it potentially compliant, but still requires verification of timing.

Action required: - Review the timing of the deforestation (check deforestation_start date) - Verify whether it's related to your supply chain - Yellow areas without blue (commodity) presence suggest the deforestation may not be directly linked to your commodity sourcing - If deforestation occurred before the EUDR cut-off date, it is compliant regardless of commodity relationship

Placeholder: Figure showing yellow (red + green) combination - deforestation in natural forest but potentially compliant

Magenta (Red + Blue): Forest Loss in Commodity Areas

What it means: Forest change detection overlapping with commodity presence.

Interpretation: This is one of the most critical combinations for EUDR compliance. It indicates deforestation occurring in areas where your target commodity is present. This combination often represents: - On-farm biomass management: Forest clearing for replanting cycles, maintenance, or crop rotation within existing commodity plantations - Forest clearing to make way for new commodity production - Potential non-compliance if the deforestation occurred after December 31, 2020

Important distinction: While magenta indicates forest loss in commodity areas, it's important to distinguish between: - Compliant operations: Deforestation that occurred before the EUDR cut-off date (December 31, 2020) - Non-compliant operations: Deforestation after the cut-off date, which violates EUDR regulations

Action required: - Verify the timing of deforestation (check the deforestation_start and deforestation_end dates in the API response) - If deforestation occurred after the EUDR cut-off date, this represents a compliance risk - Review the noncompliance_area and confidence values in the API response - Consider on-site verification for high-confidence detections - Document whether the deforestation is part of normal on-farm biomass management practices

Placeholder: Figure showing magenta (red + blue) combination - forest loss in commodity areas

Cyan (Blue + Green): Commodity in Natural Forest

What it means: Commodity presence overlapping with natural forest baseline.

Interpretation: This indicates that your commodity is being grown in areas that were natural forest in 2020. This combination suggests: - Degradation rather than clear-cut deforestation: Natural forest is being slowly replaced by commodity growing areas - Gradual conversion: The change may not be detected by breakpoint change detection algorithms (which focus on rapid, clear-cut events) - Potential compliance concern: Even if not flagged as deforestation, this represents conversion of natural forest to commodity production

Action required: - Review the biomass emissions data (available through the Biomass Emissions API) to assess gradual degradation - Verify whether the conversion occurred before or after the EUDR cut-off date - Consider this in your overall risk assessment, as degradation is also covered under EUDR definitions

Placeholder: Figure showing cyan (blue + green) combination - commodity presence in natural forest areas

White (Red + Blue + Green): All Three Layers Overlap

What it means: Forest change detection, commodity presence, and natural forest baseline all overlapping in the same area.

Interpretation: This is the most critical scenario for EUDR compliance. It indicates: - Deforestation (red) is occurring - In areas where your commodity is present (blue) - Within what was natural forest in 2020 (green)

This represents the highest risk scenario: deforestation of natural forest for commodity production after the EUDR cut-off date.

Action required: - Immediate review required: This combination should trigger a detailed investigation - Verify the exact timing of deforestation (check API response dates) - Review the noncompliance_area, confidence, and deforestation_alert values - For high-confidence detections, consider on-site verification - Document your due diligence process for audit purposes

Placeholder: Figure showing white (red + blue + green) combination - all three layers overlapping

Plot Geometry Outlines

The plot boundaries are always rendered on top of the colored layers as white or black outlines. This ensures clear visibility of: - The exact area being assessed - How detected changes relate to your plot boundaries - Whether detections are within your plots or in surrounding areas

Important: The API response values (like noncompliance_area) only report changes within the plot boundaries. However, the thumbnail shows changes in the surrounding area for context and risk assessment.

Interpreting Plot-Level Thumbnails

Plot-level thumbnails show deforestation detection for individual farm plots or parcels. Use these to:

1. Verify geo-referencing accuracy: If detections appear only along plot borders, the plot boundaries may be approximate
2. Assess compliance risk: Look for red, magenta, or white areas within your plot boundaries
3. Understand context: Even if detections are outside your plot, nearby deforestation indicates regional risk
4. Cross-reference with API values: Compare what you see in the thumbnail with the noncompliance_area, confidence, and deforestation_alert values

Common Scenarios

Scenario 1: Clean Plot - No red, magenta, or white areas within plot boundaries - Green areas may be present (natural forest) - Blue areas may be present (commodity) - Interpretation: Low deforestation risk, likely compliant

Scenario 2: Border Detections - Red or magenta pixels appear primarily along plot edges - Interpretation: May indicate geo-referencing issues or spillover from adjacent areas. Review plot boundary accuracy.

Scenario 3: Internal Deforestation - Red, magenta, or white areas clearly within plot boundaries - Interpretation: Deforestation detected within your plot. Review timing and commodity relationship.

Placeholder: Figure showing plot-level thumbnail with various color combinations

Interpreting Supply-Shed Level (Stats) Thumbnails

Supply-shed level thumbnails show aggregated deforestation patterns across larger statistical regions such as: - Administrative units (provinces, districts, municipalities) - Watersheds - Custom statistical regions

These thumbnails help you understand: - Regional deforestation patterns: Where deforestation is occurring across your supply shed - Spatial relationships: How deforestation relates to commodity plot locations - Context for plot-level assessments: Whether individual plot detections are part of broader regional patterns

Key Differences from Plot-Level Thumbnails

1. Larger geographic scope: Cover entire regions rather than individual plots
2. Aggregated data: Show patterns across multiple plots and surrounding areas
3. Regional context: Help identify hotspots and trends across your supply chain
4. Commodity plot locations: May show the distribution of your commodity plots within the region

How to Use Stats Thumbnails

1. Identify hotspots: Look for concentrations of red, magenta, or white areas
2. Compare to plot locations: See how deforestation relates to where your commodity is grown
3. Assess regional risk: Understand whether deforestation is widespread or localized
4. Prioritize investigations: Focus detailed plot-level reviews on high-risk regions

Placeholder: Figure showing supply-shed level thumbnail with regional deforestation patterns and commodity plot locations

Best Practices for Interpretation

1. Always Review Thumbnails

Don't rely solely on numerical values. The thumbnails provide crucial context that numbers alone cannot convey: - Spatial patterns - Relationship to plot boundaries - Regional context

2. Cross-Reference Multiple Sources

Combine thumbnail interpretation with: - API response values (noncompliance_area, confidence, deforestation_alert) - Biomass emissions data (for degradation assessment) - Temporal information (deforestation_start, deforestation_end)

3. Consider Confidence Levels

The API provides confidence levels (very low, low, medium, high, very high). Use these to prioritize: - High/Very High confidence: Prioritize for detailed review - Low/Very Low confidence: May indicate false positives or geo-referencing issues

4. Verify Timing

EUDR only applies to deforestation after December 31, 2020. Check the deforestation_start date to verify whether detected changes are relevant for compliance.

5. Document Your Process

For audit purposes, document: - Which thumbnails you reviewed - Your interpretation of color combinations - Actions taken based on findings - On-site verification results (if applicable)

Common Questions

Why don't I see blue (commodity) in my thumbnail?

The blue commodity layer only appears when: - A collection_hash is provided in the API request - Commodity information is available from your collection metadata - The system can identify your specific commodity type

If blue is missing, the system defaults to assuming commodity presence for backward compatibility, but you won't see the visual commodity layer.

What if deforestation is detected but there's no commodity (blue)?

If you see red (deforestation) but no blue (commodity), it suggests: - The deforestation may not be related to your commodity - The commodity layer couldn't be generated (missing collection_hash or metadata) - The deforestation is in a different area than your commodity production

In this case, the API will automatically flag the confidence as "low" and the alert as "non-critical" since the deforestation isn't clearly linked to your commodity.

How accurate are these detections?

The detection system combines multiple authoritative datasets: - 10m resolution change detection (Epoch's Dynamic World-CCDC) - 30m resolution annual forest loss (GFW-GLAD, JRC-TMF) - Multiple natural forest baselines

However, always consider: - Geo-referencing accuracy of your plot boundaries - The confidence level provided in the API response - The need for on-site verification for high-risk cases

Can I use these thumbnails for official EUDR reporting?

The thumbnails are visual aids to support your due diligence process. For official EUDR reporting, you should: - Use the quantitative values from the API response - Document your interpretation process - Include thumbnails as supporting evidence - Conduct on-site verification when appropriate

Summary

Deforestation check thumbnails are powerful tools for understanding EUDR compliance risks in your supply chain. By understanding the color-coding system and how to interpret combinations, you can:

• Quickly identify high-risk areas
• Understand the relationship between deforestation and commodity production
• Prioritize investigations and verification efforts
• Support your due diligence documentation

Remember: Always combine visual interpretation with the quantitative data provided in the API response, and document your assessment process for audit purposes.