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Annual Biomass Stock and Change Data for National REDD+ Forest Reference Emission Levels: A Direct Estimation Approach

  • Wildlife Works
  • 3 hours ago
  • 5 min read


Originally prepared by Wildlife Works Carbon and Chloris Geospatial  in October 2025


Introduction

 Forest Reference Emission Levels (FRELs) are the benchmarks against which emission reductions under REDD+ are measured. They are expressed in tonnes of CO₂-equivalent (tCO2e) per year for a reference period and form the basis for results-based payments. However, most FRELs still rely on activity-data × emission-factor (AD×EF) methods. These depend on visually interpreted satellite images and ground-based emission factors, which are coarse and often omit degradation. 

Wildlife Works Carbon (WWC) and Chloris Geospatial propose a modern approach to FREL construction using direct biomass measurement. Rather than counting hectares and applying emission factors, this approach measures carbon stock and change at the pixel level using multi-sensor remote sensing (LiDAR + multispectral imagery) and machine-learning algorithms. This directly captures degradation and regeneration, enabling nested baselines that align with project-level monitoring. The approach builds on lessons from a pilot in Chile and offers governments a faster, cheaper, and more accurate path to FREL construction. 


Limitations of Current FREL Methods 

  • Omission of degradation and reliance on visual interpretation introduce human error. 

  • Coarse emission factors mask spatial heterogeneity and uncertainty. 

  • AD×EF methods are slow, expensive, and not spatially explicit. 

  • Many baselines are outdated, limiting responsiveness to changing forest dynamics. 


Direct Biomass Measurement: Proposed Approach 


Multi-sensor data: Uses LiDAR (GEDI/IceSAT), airborne LiDAR, and multispectral imagery (Landsat, Sentinel-2) calibrated to national forest inventory plots. 


Calibration: Uses existing ground plots and LiDAR for accuracy, drastically reducing the need for new field data. 


Speed: Once calibrated, a FREL for an area the size of Pará, Brazil, can be produced in 30 minutes. 


Back-calculation: Activity data can be derived from the Chloris carbon stock and change dataset using the national forest definition to set biomass thresholds for deforestation and degradation, ensuring compatibility with existing FRELs. 


Alignment with UNFCCC and IPCC Guidance 

The UNFCCC encourages stepwise improvement and transparency in national FRELs. Direct biomass estimation approaches comply with this guidance by integrating historical data and supporting yearly FREL updates with modern sensors: 

Under Decision 12/CP.171, the UNFCCC instructs Parties to base their national Forest Reference Emission Levels (FRELs) and Forest Reference Levels (FRLs) on the most recent IPCC guidance.


The IPCC 2006 Guidelines for National Greenhouse Gas Inventories2 (Vol. 4 AFOLU, § 2.3.1) define two approaches for estimating changes in biomass carbon stocks: the gain-loss method and the stock-difference (stock-change) method, the latter estimating emissions and removals as the difference in measured biomass carbon stocks at two points in time.


The 2019 Refinement to the 2006 Guidelines3 reaffirms this and explicitly states that carbon-stock changes may be derived from repeated measurements or repeated observations, noting that Tier 3 methods may employ models or measurement systems, including remote-sensing approaches, that provide spatially explicit information. Because Decision 14/CP.194 requires REDD+ measurement, reporting, and verification systems to quantify forest carbon stocks and their changes consistent with IPCC guidance, the use of remote-sensing-based stock-change methods is permitted for FREL construction under the UNFCCC framework. 



Implementation Path for Governments 

  1. Acquire Chloris remote sensing data for the jurisdiction. 

  2. Validate and calibrate using existing forest inventory plots. 

  3. Compute carbon stock and change Forest Reference Emission Level (FREL) for the chosen reference period. 

  4. Equitable Earth generates spatially explicit risk maps using the same dataset for project nesting. 

  5. Build national capacity through training and technical transfer. 

  6. Update the FREL yearly as Chloris publishes new data. 


Benefits to Governments 

  • Comprehensive baselines wholistically capturing historical emissions, inclusive of degradation, regeneration, and subtle forest changes. 

  • Faster and cheaper FREL generation. 

  • Transparent and auditable data aligned with IPCC and UNFCCC guidance. 

  • Enables nested REDD+ projects and reduces dependence on donors and multi-lateral development aid. 

  • Supports comprehensive annual FREL updates for the UNFCCC stepwise approach. 


Benefits to National REDD+ Programs 

  • Enables “true” nesting of Equitable Earth projects into national REDD+ systems. 

  • Unlocks institutional buyers (LEAF, IGC) through jurisdictional nested REDD+ (JREDD). 

  • Demonstrates leadership in carbon science and remote sensing. 

  • Promotes broader acceptance of carbon stock & change methodologies in JREDD standards and methodologies, 

  • Aligns projects with national climate goals (nesting), allowing national governments to harness project performance. 


Examples of Degradation Significance 

Empirical results from Chloris datasets show degradation emissions often exceed deforestation across multiple jurisdictions. The table below summarizes the most recent 10‑year Jurisdictional Reference Level (JRL) analyses for four jurisdictions: Zambia, Pará (Brazil), Colombia, and the Democratic Republic of the Congo - based on Chloris Stock & Change datasets and forest thresholds. 


Table 1. Forest Reference Emission Levels (FRELs) for 4 Jurisdictions 

Jurisdiction 

Historical Reference Period 

Deforestation (MtCO₂e/yr) 

Degradation (MtCO₂e/yr) 

Total JRL (MtCO₂e/yr) 

% Degradation 

RMS Uncertainty (tCO₂e/ha/yr) 

Zambia 

2015 – 2024 

34.25 

111.43 

145.69 

76 % 

18.63 

Pará, Brazil 

2013 – 2022 

165.29 

289.04 

454.33 

64 % 

32.66 

Colombia 

2013 – 2022 

81.11 

202.33 

283.44 

71 % 

30.44 

DemocraticRepublic of the Congo (DRC) 

2014 – 2023 

199.38 

561.09 

760.47 

74 % 

48.40 


These findings reveal that degradation consistently represents between 63% and 76% of total forest‑related emissions across diverse biomes, highlighting why direct biomass measurement is essential for complete and accurate FRELs and REDD+ accounting. 


Policy Environment and Challenges 

UNFCCC Decision 1/CP.165 calls on developing countries to develop transparent, periodically updated FRELs. While consistent with this guidance, challenges remain: 

  • Most standards (e.g., ART/TREES) still do not permit carbon stock & change data. 

  • Many governments rely on FAO/UNDP systems rooted in AD×EF methodologies. 

  • Auditability concerns persist, but can be mitigated through robust validation protocols. 

  • Policy alignment is needed with national definitions and forest classification schemes. 

 

Figure 1-4: Deforestation and Degradation Data for Colombia, Zambia, Para State of Brazil, and DRC.

 

Strategic Opportunities and Next Steps: 

  • Pilot demonstrations of direct biomass FRELs: Chloris and Wildlife Works can work with interested governments or government partners to demonstrate jurisdictional-scale FRELs using national forest definitions and local calibration data. 

  • Example datasets and spatial analyses: Participating governments can access examples of national-scale results, including comprehensive FREL metrics and spatially explicit maps of historical deforestation and degradation. 

  • Collaborative testing and knowledge transfer: Countries may choose to participate in joint trials or request training to run the methodology independently. These collaborations can include knowledge transfer, technical support, or full implementation. 

  • Validation and funding discussions: Partners can jointly explore funding options or undertake validation exercises with relevant standards (ART/TREES, FCPF) to support adoption and scale-up. 

  • Capacity-building and technical workshops: Chloris and Wildlife Works can organize focused sessions to build capacity within national MRV teams and government agencies using these datasets. 

 

Conclusion 

Traditional AD×EF FREL methods omit degradation and rely heavily on both field data and manual interpretation. This process can often be cumbersome and expensive, creating coarse and outdated baselines. Direct biomass measurement method leverages active remote sensing like LiDAR to capture carbon dynamics at the pixel level. This enables accurate, auditable, and rapidly updatable baselines aligned with global IPCC standards. Adopting this approach can strengthen national REDD+ programs, unlock climate finance, and align project-level and national carbon accounting. 


Accessing Chloris Biomass Stock and Change Data and Technical Demonstrations 

Chloris Geospatial and Wildlife Works welcome inquiries from national governments and government partners interested in exploring biomass stock and change data for REDD+ program development. 


Available Support: 

  • Technical demonstrations: Jurisdiction-specific examples showing historical deforestation and degradation patterns, FREL calculations, and spatially explicit biomass stock and change maps 

  • Data access: Sample datasets calibrated to national forest definitions and existing forest inventory data 

  • Methodology workshops: Training sessions for national MRV teams on data processing, validation protocols, and FREL construction 

  • Validation support: Collaborative testing against ground-truth data and existing national forest inventories 

  • Implementation planning: Technical guidance on integration with existing national monitoring systems 


To Request Information: 

Chloris Geospatial 

Alessandro Baccini / Co-Founder, Co-CEO and CSO 

 

Wildlife Works Carbon 

Jeremy Freund / Chief Climate Officer 



 

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