Methodology Inputs Comparison

Forest / AFOLU Carbon Methodology Inputs — Comparison Matrix

Author: Research compiled for C6 quantification model design Date: 2026-05-07 Scope: Verra VCS (legacy + consolidated), ART TREES, Plan Vivo PV Climate, Gold Standard LUF, CDM A/R, IPCC 2006 GL + 2019 Refinement Goal: Identify the true core of carbon-quantification inputs across methodologies, the methodology-specific extensions, and realistic LATAM data sources. Use this to design a coherent project input schema without conflating terms.

Reading note. Carbon pools below follow IPCC 2006 / VCS canonical naming: AGB = above-ground (live tree) biomass; BGB = below-ground (root) biomass; DW = dead wood (standing + lying); L = litter; SOC = soil organic carbon; HWP = harvested wood products. “Activity data × emission factor” (AD×EF) is the universal accounting frame inherited from IPCC.

1. Unified comparison table

One row per required input per methodology. ~110 rows.

#	Methodology	Activity	Input	Why it’s needed	Data source	Notes
1	IPCC 2006 GL + 2019 Refinement (Vol. 4 AFOLU)	Framework (REDD/ARR/IFM/Cropland/Grassland)	Land-use category × land-use transition matrix (6 LU classes × 6 = 36 transitions)	Core AD×EF accounting structure inherited by every methodology below	National land cover map; LULC transition matrix from satellite (e.g. MapBiomas, ESA WorldCover)	IPCC 2006 Vol. 4 Ch. 3
2	IPCC 2006 GL	Framework	Tier 1/2/3 default carbon stock factors per biome (t C/ha) for AGB, BGB	Tier 1 fallback when no local plot data	IPCC 2006 Vol. 4 Ch. 4 Tables 4.7, 4.8, 4.12; FAO Global Ecological Zones map	Tier 1 = pantropical defaults, Tier 2 = country-specific, Tier 3 = model + plots
3	IPCC 2006 GL	Framework	Root-to-shoot ratio (R) by biome	Convert AGB → BGB when no field roots data	IPCC 2006 Vol. 4 Table 4.4; Mokany et al. 2006	Tropical moist forest R ≈ 0.37
4	IPCC 2006 GL	Framework	Carbon fraction (CF, t C / t dry matter)	Convert biomass → carbon	IPCC default = 0.47 (often 0.5); Martin & Thomas 2011	Mandatory in every methodology below
5	IPCC 2006 GL	Framework	Wood basic density (ρ, t/m³) by species or genus	Convert volume or DBH → biomass via allometric	Global Wood Density Database (Zanne et al. 2009); national forest inventory	Required for every allometric that takes ρ as covariate
6	IPCC 2006 GL	Framework	Biomass expansion factor (BEF), biomass conversion factor (BCF)	Convert merchantable volume → total AGB	IPCC 2006 Vol. 4 Tables 4.5; national species data	Used in volume-based inventories
7	IPCC 2006 GL	Framework	Default emission factors for non-CO₂ (CH₄, N₂O) from biomass burning	Fire emissions in deforestation/site prep	IPCC 2006 Vol. 4 Ch. 2 Table 2.5	Combustion factor + emission factor
8	IPCC 2019 Refinement	Framework	Updated SOC reference stocks (0–30 cm) by climate × soil class	More recent SOC defaults	IPCC 2019 Ch. 2 Vol. 4	Often used by ARR/grassland methodologies
9	IPCC 2019 Refinement	Framework	Updated GWP100 values	Convert CH₄/N₂O to CO₂e	IPCC AR6 (28 for CH₄, 273 for N₂O)	Verra now mandates AR6 GWPs
10	Verra VM0007 (REDD+ MF v1.6/1.7/1.8)	REDD (avoided unplanned + planned deforestation, degradation, ARR-on-forest, peatland, tidal wetland)	Reference region polygon	Spatial frame for historical deforestation rate	Project proponent + GIS analysis	Modular: pick BL-UP, BL-PL, BL-DFW, BL-ARR, BL-PEAT, BL-TW
11	VM0007	REDD	Project area + leakage belt polygons	Spatial accounting boundaries	Project proponent	Leakage belt sized per VMD0010 (LK-ASU)
12	VM0007	REDD	10–15 yr historical LULC time series in reference region	Establish baseline deforestation rate	Landsat/Sentinel-2 time series; MapBiomas; INPE PRODES	Min 2 historical maps required
13	VM0007 (VMD0007 BL-UP)	REDD-AUD	Baseline deforestation rate (ha/yr) projection	Baseline emissions denominator	Historical avg; linear/non-linear regression; simulation	Project-set (this is what Verra removed in VM0048)
14	VM0007 (VMD0006 BL-PL)	REDD-Planned	Documented agent’s deforestation plan + carbon stock change schedule	Planned deforestation baseline	Concession docs, gov’t plans, satellite
15	VM0007 (VMD0001 CP-AB)	REDD/ARR	Above-ground biomass (t d.m./ha) by stratum	Emission factor for forest loss	Field plots (DBH, height, species) + allometric (e.g. Chave 2014)	Mandatory
16	VM0007 (VMD0001)	REDD/ARR	Below-ground biomass (t d.m./ha) by stratum	Roots emission factor	AGB × R (IPCC root-shoot) or direct excavation	Mandatory if non-negligible
17	VM0007 (VMD0002 CP-D)	REDD	Dead-wood pool (t d.m./ha)	DW emission factor	Line-intersect sampling for lying DW; plot for standing DW	Mandatory unless conservatively excluded
18	VM0007 (VMD0003 CP-L)	REDD	Litter pool (t d.m./ha)	Litter emission factor	0.25 m² destructive sampling on plots	Often excluded as de minimis
19	VM0007 (VMD0004 CP-S)	REDD-peat / wetland	SOC stock (t C/ha)	Soil emission factor	Cores 0–30 cm + bulk density + %C	Mandatory in peat/wetland; usually optional in mineral soil REDD
20	VM0007 (VMD0005 CP-W)	REDD-IFM/Logging	HWP carbon (t C)	Long-term wood-product carbon retention	Mill records, retention factors (Winjum 1998; IPCC HWP)	Optional
21	VM0007 (VMD0016 X-STR)	All	Stratification map (forest types × disturbance class)	Reduce variance of EFs	Field + remote sensing classification	Required
22	VM0007 (VMD0017 X-UNC)	All	Uncertainty propagation per pool (95% CI)	Apply confidence-interval deduction	Plot-level variance	Deduction if total uncertainty > 15%
23	VM0007 (VMD0010 LK-ASU)	REDD-AUD	Leakage belt LULC time series	Detect activity displacement to belt	Same satellite stack as project area
24	VM0007 (VMD0011 LK-ME)	REDD-AUD	Market-effects leakage factor (% of avoided emissions)	Account for commodity-market displacement	Default tables in VMD0011; sometimes economic modelling
25	VM0007 (VMD0013 E-BPB)	REDD	Burn area (ha), biomass density, combustion completeness, emission factors for CH₄/N₂O	Non-CO₂ fire emissions	Active-fire products (MODIS/VIIRS), burn-scar mapping, IPCC defaults
26	VM0007 (VMD0015 M-REDD)	REDD	Monitoring frequency: ex-post LULC at every verification (≤ 5 yr)	Project performance	Satellite + plots
27	Verra VM0009 v3.0	Avoided ecosystem conversion (forest, grassland, shrubland)	8 baseline-type taxonomy choice (ecosystem × agent × driver × identifiability × progression)	Determines which baseline approach + leakage	Project proponent + driver analysis	Wildlife Works methodology
28	VM0009	Avoided conversion	Fixed-area sample plots in project + proxy areas	AGB, BGB, DW, L, SOC stocks	Field plots; line-intersect for lying dead wood
29	VM0009	Avoided conversion	SOC samples from cores or pits	SOC stock change with ecosystem loss	Soil cores within biomass plots; default SOC decay function
30	VM0009	Avoided grassland/shrubland conversion (ACoGS)	Native grassland baseline cover + species composition	Establish that area is native/non-converted	Aerial photos, historical satellite, regional ecological maps	Unique to VM0009 v3.0
31	Verra VM0015 v1.2	Avoided unplanned deforestation (mosaic + frontier)	Reference region polygon (large enough to capture deforestation drivers)	Spatial frame for historical rate	Driver-based delineation; FAO/national LU maps	Excludes degradation (only AUD)
32	VM0015	AUD	Project area + leakage belt + leakage management areas	Spatial accounting	Project proponent; leakage belt typically 10–20 km buffer
33	VM0015	AUD	10–15 yr LULC change maps (≥ 3 time points) in reference region	Historical deforestation rate trend	Landsat time series; INPE PRODES, MapBiomas
34	VM0015	AUD	Spatial allocation model for baseline deforestation (logistic regression, Land Change Modeler, Dinamica EGO)	Project-area-specific risk	Driver layers: distance to roads/rivers/settlements, slope, elevation, prior loss, land tenure	The piece Verra centralized in VM0048
35	VM0015	AUD	Allocation algorithm validation (figure-of-merit)	Demonstrate model skill	Held-out historical years
36	VM0015	AUD	Carbon stock per stratum (AGB, BGB, DW, L, optional SOC)	Emission factor	Field plots + allometric (Chave 2014 for tropics)	Same pool list as VM0007
37	VM0015	AUD	Driver-of-deforestation analysis (qualitative + quantitative)	Justify baseline & leakage	Field interviews, gov’t reports, prior studies
38	Verra VM0048 v1.0	REDD (framework)	Project area polygon (within an eligible jurisdiction)	Required for risk-map allocation	Project proponent	Replaces VM0007 BL-UP & VM0015 baseline-setting
39	VM0048 + VMD0055	REDD-AUD	Jurisdictional Activity Data (JAD): historical deforestation per year, per jurisdiction (10-yr reference period)	Set total deforestation envelope	Verra-supplied (developed under VMD0055 RFP, e.g. Brazil states)	Project no longer estimates this — fee-based access
40	VM0048 + VMD0055	REDD-AUD	Forest Cover Benchmark Map (FCBM) at 3 time points across reference period	Define forest extent + change	Verra-supplied (jurisdictional)	Replaces project-level historical maps
41	VM0048 + VMD0055	REDD-AUD	Allocated Deforestation Risk Map (per pixel)	Distributes JAD to project area pro-rata by risk	Verra-supplied; modelled from drivers (distance to clearing, road, slope, etc.)	Project’s baseline = sum(risk-allocated activity over project pixels)
42	VM0048	REDD-AUD	Project-specific Emission Factor (EF) per stratum: AGB stock pre-deforestation (t C/ha)	Apply to allocated activity	Field plots + allometric, OR existing remote-sensing biomass map (GEDI L4A AGBD, ESA CCI Biomass)	This is the residual project measurement under VM0048
43	VM0048	REDD-AUD	Mandatory carbon pools: AGB + BGB; DW, L, SOC if non-negligible	Pool-level EF	Field; plus excludable-as-de-minimis test in Appendix 1	Stricter pool-completeness language than VM0007
44	VM0048	REDD-AUD	Forest stratification within project (by forest type × disturbance)	Pool-specific EF	Project field + RS classification	Required even though activity data is jurisdictional
45	VM0048	REDD-AUD	Project monitoring: ex-post hectares deforested in project + leakage area	Compare actual vs allocated baseline	Sentinel-1/2, PlanetScope; ≥ annual cadence	New stricter monitoring — annual or biennial
46	VM0048	REDD-AUD	Uncertainty: combined activity-data + emission-factor uncertainty (95% CI)	Conservative deduction	Plot variance, RS classification accuracy, JAD variance	Quantitative deduction applied at each issuance
47	VM0048 + LK module	REDD-AUD	Leakage belt activity data (per same RS protocol as project)	Activity-shift leakage	Project monitoring + jurisdictional data
48	VM0048 + LK module	REDD-AUD	Market-leakage factor	Commodity-market leakage	Default factors per driver (cattle, soy, etc.)
49	VM0048	REDD-degradation (when degradation module released)	Forest degradation activity data	Future module under development	Higher-resolution RS (GEDI, Sentinel-1, ICESat-2)	Not yet operational as of 2024
50	Verra VM0047 v1.1 (area-based)	ARR	Project area polygon meeting non-forest-for-≥10-yr OR degraded-forest test	Eligibility	Historical satellite (Hansen GFC, MapBiomas)	v1.1 expanded to degraded forest
51	VM0047 (area-based)	ARR	Donor pool definition: jurisdictional boundary, ecoregion, policy, land tenure	Source of matched control plots	Project proponent + ancillary GIS
52	VM0047 (area-based)	ARR	Stocking Index (SI) — biomass-based, not NDVI/NDFI — at 3 time points pre-start	Match project to control plots	Remote-sensing AGB product (e.g. GEDI L4B, Chloris, Kanop, Planet biomass)	Defines project’s pre-start trajectory
53	VM0047 (area-based)	ARR	Matched control plots via k-NN matching on multivariate distance	Dynamic performance benchmark = counterfactual	Algorithmic; matches without replacement	New paradigm vs static baseline
54	VM0047 (area-based)	ARR	Annual SI monitoring, project + control, every verification	Crediting baseline + project change	Same RS product, annual cadence	Crediting only against project − control delta
55	VM0047	ARR	Common-practice benchmark (15% adoption test)	Additionality	Sub/national land-use statistics	If activity is common practice, project not additional
56	VM0047	ARR	Mandatory: AGB and BGB pools	Removals carbon	Field plots + allometric (Chave 2014, regional eqs); BGB via R or Cairns 1997
57	VM0047	ARR	Optional / conditional: non-woody biomass (plot-based), SOC (direct measurement)	Pool completeness	Plot sampling + soil cores	Conditional per Table 1 of VM0047
58	VM0047	ARR	Wood density (ρ, t/m³) per species	Allometric input	Global Wood Density DB; species-specific where available
59	VM0047	ARR	Carbon fraction (CF, default 0.47 or species-specific)	Biomass → carbon	IPCC default or measured
60	VM0047	ARR	Pre-existing woody biomass measurement (if removed)	Net accounting of clearance	Field inventory before site prep	New in v1.1
61	VM0047	ARR	Site-prep emissions: biomass burning + fertilizer (N₂O) + fossil fuel	Project emissions	IPCC EFs; project records
62	VM0047 (census-based)	ARR (urban, agroforestry, shelterbelt, dispersed)	Full census of plantings (GPS or marker per tree)	Stock change tree-by-tree	Field GPS, photo evidence	No leakage applicable
63	VM0047 + VMD0054	ARR (area-based)	Pre-project land use/production (3 yr or 1 crop rotation)	Leakage baseline	Field + statistics	Mandatory for area-based; exempt for census
64	VM0047 + VMD0054	ARR	Net production replaced (commodity tonnes shifted)	Market-effects leakage	National stats; field surveys
65	VM0047 + VMD0054	ARR	New forest cleared for displaced production (5 yr post-start)	Activity-shift leakage	Satellite monitoring of leakage area
66	VM0047	ARR	Uncertainty: pool-level variance, propagated; matching uncertainty (gap noted by ICVCM)	Deduction at issuance	Plot variance + RS biomass uncertainty
67	ART TREES 2.0	Jurisdictional REDD+ (D, FD, conservation, SMF, enhancement)	Accounting Area = national or eligible subnational jurisdiction	Whole-jurisdiction frame	Government boundary	No project-level reference region
68	ART TREES 2.0	Jurisdictional REDD+	5-year historical reference period emissions baseline	Crediting Level	National forest monitoring system + IPCC-consistent EFs	Updated every 5 yr
69	ART TREES 2.0	Jurisdictional REDD+	HFLD score (forest cover % × deforestation rate)	HFLD eligibility (score > 0.5 each yr of 5-yr reference)	National + global forest cover (Hansen, gov’t)	HFLD jurisdictions get bonus crediting
70	ART TREES 2.0	Jurisdictional REDD+	Activity Data: ha of deforestation, ha of forest degradation, ha of new forest, per stratum, annually	AD side of AD×EF	National Forest Monitoring System (NFMS); RS-based per IPCC GFOI guidance	Must be IPCC TACCC-compliant
71	ART TREES 2.0	Jurisdictional REDD+	Emission Factors per pool per forest type (t CO₂e/ha)	EF side of AD×EF	National Forest Inventory (NFI) plots; allowed: RS, models, IPCC Tier 1 defaults	Must justify tier choice
72	ART TREES 2.0	Jurisdictional REDD+	Mandatory carbon pools: AGB, BGB, DW, L, SOM (soil organic matter)	Pool completeness	NFI + IPCC defaults where data lacking	HWP excluded explicitly in TREES 2.0
73	ART TREES 2.0	Jurisdictional REDD+	Stratification by forest type	Reduce EF variance	NFI strata + RS
74	ART TREES 2.0	Jurisdictional REDD+	Uncertainty deduction: 95% CI half-width on total ER	Conservativeness	Combined AD + EF uncertainty propagation	Higher uncertainty → larger deduction
75	ART TREES 2.0	Jurisdictional REDD+	Buffer pool deduction (reversal risk)	Permanence	TREES Risk Tool	Buffer % varies per jurisdictional risk
76	ART TREES 2.0	Jurisdictional REDD+	Leakage assessment (qualitative for jurisdictions ≥ subnational; assumed minimal at national)	Avoid double counting	Border activity analysis, trade flows
77	ART TREES 2.0	Jurisdictional REDD+	REDD+ Implementation Plan (locations of activities)	Programmatic linkage	Government policy docs
78	ART TREES 2.0	Jurisdictional REDD+	Cancun Safeguards self-reporting + Safeguards Information System (SIS)	Required for crediting	Government social/env safeguard reports	LEAF Coalition demands additional rigor
79	ART TREES 2.0	Jurisdictional REDD+	Annual monitoring; verification ≤ every 2 yr	Performance tracking	Updated NFMS + activity data
80	Plan Vivo PV Climate v5 (Methodology Requirements 1.0)	ARR / forest restoration / agroforestry / cropland practices	Project area (community-managed land, often smallholder)	Project boundary	GPS field; sometimes community mapping
81	Plan Vivo PV Climate	ARR/agroforestry	Carbon pools required per Methodology Requirement 2.2.2: AGB + BGB; DW, L, SOC where significant	Removals per pool	Field plots; Tier 1 defaults allowed for smallholder	More flexibility for smallholder than VM0047
82	Plan Vivo PV Climate	ARR/agroforestry	Approved methodology selection (e.g. PV-Climate-AR, PV-Climate-AF)	Activity-specific calc engine	Plan Vivo registry
83	Plan Vivo PV Climate	ARR/agroforestry	Carbon Indicators (Req 4.2): annual planting records, survival rate, growth measurements	Periodic monitoring of removals	Community monitors + technical coordinator
84	Plan Vivo PV Climate	All	Livelihood Indicators (Req 4.3)	Required for issuance — co-benefits central	Household surveys, focal group	Distinguishes Plan Vivo from VCS/ART
85	Plan Vivo PV Climate	All	Ecosystem Indicators (Req 4.4)	Biodiversity / landscape health	Field + RS
86	Plan Vivo PV Climate	All	PRA-derived (Participatory Rural Appraisal) baseline of land use + livelihoods	Counterfactual for community + carbon baseline	Community workshops, household surveys	Plan Vivo signature: community-set baseline
87	Plan Vivo PV Climate	All	Crediting baseline (Methodology Requirement 1.5.1): conservative model-based	Avoid over-crediting	Approved Plan Vivo Tools (e.g. growth curves, default factors)	Conservative assumptions required
88	Plan Vivo PV Climate	All	Uncertainty: must be disclosed but smaller-project default factors allowed	Conservativeness	Plan Vivo Tools + IPCC	Often Tier 1
89	Plan Vivo PV Climate	All	Risk buffer (often 10–20%)	Reversal/permanence	Plan Vivo Risk Tool
90	Plan Vivo PV Climate	Cropland practices	Soil organic carbon model inputs (climate, soil, management)	SOC change	RothC, IPCC Tier 1, or measured
91	Gold Standard LUF — A/R Methodology v2.0 (403 v2.0)	A/R	Project area meeting host-country forest definition test	Eligibility (was non-forest at start)	National forest definition + satellite
92	GS LUF A/R	A/R	Trees ≥ 2 m height target	Project must achieve forest cover	Field measurement, plot sampling
93	GS LUF A/R	A/R	Crediting period 30–50 yr	Long-term planning	Project design choice
94	GS LUF A/R	A/R	Mandatory pools: AGB, BGB	Removals	Field plots + allometric
95	GS LUF A/R	A/R	Optional pools: DW, L, SOC (depending on baseline)	Pool completeness if material	Field measurement
96	GS LUF A/R	A/R	Allometric equations: project-specific or region-appropriate	AGB conversion	Chave 2014, regional eqs (e.g. Brown 1997, Cairns 1997 for BGB)
97	GS LUF A/R	A/R	Biomass expansion factor (BEF) — when using volume inventories	Volume → AGB	National forest inventory; IPCC defaults
98	GS LUF A/R	A/R	Root-shoot ratio (R)	AGB → BGB	IPCC 2006 Table 4.4; regional studies
99	GS LUF A/R	A/R	Fertilizer N input (kg N/ha)	N₂O emissions per IPCC Tier 1 (EF1)	Project records
100	GS LUF A/R	A/R	Biomass burning area + EF (CH₄, N₂O)	Site-prep non-CO₂ emissions	Project records + IPCC
101	GS LUF A/R	A/R	Monitoring plot network	Periodic stock change	Permanent sample plots; Winrock/CDM sourcebook
102	GS LUF A/R	A/R	Uncertainty target	Quality	Typically ±15% at 95% CI; deduction otherwise
103	GS LUF A/R	A/R	Leakage assessment (activity displacement)	Net removals	Community surveys; market analysis
104	GS LUF A/R	A/R	Buffer pool contribution	Permanence	GS Risk Tool
105	CDM AR-AMS0007 (small-scale A/R, lands other than wetlands)	Small-scale A/R	Stratification by tree species (or species groups) and age	EF precision	Project planting plan
106	CDM AR-AMS0007	Small-scale A/R	Allometric equations per species/group + DBH measurements	AGB per tree	Field plots; species-specific eqs from literature
107	CDM AR-AMS0007	Small-scale A/R	Remote-sensed map for ex ante and ex post stratification	Strata mapping	Landsat/Sentinel-2
108	CDM AR-AMS0007	Small-scale A/R	AR-Tool14 (Estimation of carbon stocks in trees & shrubs) parameters: ρ, BEF, R, CF	Stock per pool	CDM tool tables; IPCC defaults	Mostly Tier 1/2
109	CDM AR-AMS0007	Small-scale A/R	Baseline biomass: pre-project trees, shrubs, herbaceous (often assumed ≈ 0 if cropland/grassland)	Baseline removal stock	Field check
110	CDM AR-AMS0007	Small-scale A/R	Leakage from displacement of pre-project activity (limited displacement variants)	If grazing or cropping displaced	Field surveys
111	CDM AR-AMS0007	Small-scale A/R	Monitoring plots, fixed area, permanent	Stock change tracking	Standard CDM protocol
112	CDM AR-AMS0007	Small-scale A/R	tCER/lCER issuance schedule	Permanence (CDM-specific temporary credits)	Periodic verification	Unique to CDM A/R; not used by Verra/ART

2. Summary

2.1 The “true core” — inputs every methodology requires

Across all eight methodologies, the same skeleton is always present. If C6 is designing a generic input schema, these are the slots that must exist:

Project geometry: project area polygon (always); reference region / leakage belt / accounting area (REDD-specific but conceptually a wider polygon).
Stratification: forest type × disturbance × age (or planted species × age for ARR). Every methodology requires this for both AD and EF estimation.
Activity Data: hectares of land-use transition per stratum per year. The unit is invariant — what differs is whether it’s historical (baseline) or project-period (monitoring), and whether it’s jurisdictional (VM0048, ART TREES) or project-set (everyone else).
Emission Factors per carbon pool in t C/ha (or t CO₂e/ha): AGB, BGB, DW, L, SOC, HWP. Every methodology specifies which of these are mandatory vs optional, but the data structure is identical.
Allometric machinery: DBH, height, wood density (ρ), carbon fraction (CF), root-shoot ratio (R), biomass expansion factor (BEF), and a chosen allometric equation (Chave 2014 is the dominant tropical default).
Plot inventory: permanent sample plots with measurement protocol, plot-level variance for uncertainty propagation.
Uncertainty: 95% CI half-width per pool, propagated to total emission/removal, with a conservativeness deduction triggered if uncertainty exceeds the threshold (commonly ±15%).
Leakage: activity-shift leakage (from monitoring a leakage belt) + market-effects leakage (default factor or model).
Buffer / non-permanence reserve: % deduction based on a methodology-specific risk tool.

If C6’s data model captures these eight buckets cleanly, every methodology can be expressed as a configuration on top.

2.2 Methodology-specific inputs (where terms get conflated)

These are the inputs unique to specific methodologies — they are the most common source of confusion when copying terms across:

VM0015 only: spatial allocation model (Dinamica EGO, Land Change Modeler) producing a project-specific deforestation risk map; figure-of-merit validation. Replaced under VM0048 by the Verra-supplied allocated risk map.
VM0048 + VMD0055: Forest Cover Benchmark Map (FCBM, jurisdictional), Allocated Deforestation Risk Map (jurisdictional), Jurisdictional Activity Data (JAD). These are Verra-supplied inputs, not project-derived. The project’s emission factor estimation is all that remains as the field-level input — opposite of VM0007/VM0015 where the project sets the baseline rate.
VM0047 only: matched control plots, k-NN matching algorithm, Stocking Index (biomass-based, not NDVI-based), dynamic performance benchmark (recomputed each verification). The “baseline” is statistical, not historical.
ART TREES 2.0 only: HFLD score, accounting area = jurisdiction, no project-level reference region. Pool list mandates SOM (soil organic matter, broader than SOC) and excludes HWP explicitly.
Plan Vivo only: PRA-derived baseline, mandatory Livelihood and Ecosystem Indicators (carbon alone is insufficient for issuance), community monitor protocol.
Gold Standard A/R only: trees-≥-2 m target, mandatory N₂O fertilizer accounting, mandatory crediting period 30–50 yr.
CDM only: tCER/lCER temporary-credit schedule (replaced by buffer in Verra/ART/PV).

2.3 Biggest divergences: Verra legacy vs Verra new (the active migration)

Dimension	VM0007 / VM0009 / VM0015 (legacy)	VM0048 + VMD0055 (new)
Who sets the baseline rate	Project proponent (historical or modelled)	Verra (jurisdictional, allocated per pixel)
Risk allocation model	Project-built (Dinamica EGO etc.)	Verra-supplied risk map
Forest cover map	Project-built from Landsat/Sentinel	FCBM supplied by Verra (3 time points)
Deforestation rate driver	Reference region trend	JAD jurisdictional total, allocated by risk pixel
Project’s residual measurement burden	AD + EF + driver model + spatial allocation	EF only (and project-area monitoring)
Pool completeness	Optional exclusion if conservative	Stricter: AGB+BGB always; DW/L/SOC require de minimis test
Monitoring cadence	Per VMD0015 (≤ 5 yr verification)	Annual or biennial
Uncertainty	VMD0017 propagation	Stricter combined AD+EF, with explicit deduction at issuance
Crediting fee	Per Verra base fee	Plus payment for jurisdictional data access
Practical effect	Heavy GIS/modelling team	Heavy field/RS biomass team

Practical implication for C6: under VM0048 a project-side input schema needs to consume an external risk map and JAD as primary inputs (almost like an oracle), and the historical-deforestation-rate logic from VM0007/VM0015 should be cleanly separated from the active model — otherwise the schema will silently mix legacy assumptions into VM0048 calculations.

2.4 LATAM data-source recommendations

For Brazil / Colombia / Peru context, the realistic data stack:

Activity Data (forest cover & change):
- Brazil: INPE PRODES (annual, Amazon + Cerrado, ≥ 6.25 ha MMU) for VCS legacy baselines; INPE DETER / DETER-B (near-real-time alerts) for project-period monitoring; MapBiomas Collection 10 (annual LULC, full Brazil, all biomes) for stratification + land-use history; MapBiomas Alerta for fine-grain alerts.
- Colombia: IDEAM SMByC (Sistema de Monitoreo de Bosques y Carbono); MapBiomas Colombia.
- Peru: MINAM/SERFOR Geobosques; MapBiomas Peru / RAISG for the Amazon.
- Cross-LATAM: Hansen Global Forest Change (GFC) for VCS-acceptable global benchmark; ESA WorldCover; RADD alerts (Wageningen) for tropical near-real-time degradation.
Emission Factors (biomass density):
- Field: National Forest Inventories (Brazil’s IFN, Colombia’s IFN, Peru’s INF). Integrate with project plots.
- Allometric: Chave et al. 2014 (pantropical); regional equations from EMBRAPA, CIFOR for specific biomes (Cerrado, Caatinga, Amazon várzea).
- Wood density: Global Wood Density Database (Zanne et al. 2009) — has good LATAM coverage.
- Remote sensing biomass: NASA GEDI L4A AGBD (sparse footprint, validates plots); GEDI L4B 1 km gridded; ESA CCI Biomass v5 (100 m); ICESat-2 ATL08; commercial products (Chloris, Kanop, Planet Forest Carbon Diligence) for VM0047 stocking-index work.
VM0048 jurisdictional data: Verra has finalized risk maps for Mato Grosso, Pará (Brazil) and provisional for Rondônia. Other LATAM jurisdictions are in development queue under the VMD0055 RFP — projects in Brazil’s other Amazon states, Colombia, Peru must wait or use VM0007 transition.
Drivers / ancillary: TerraClass (Amazon + Cerrado post-deforestation land use); MAAP alerts (Amazon Conservation); SIATAC; protected area boundaries (WDPA); indigenous land boundaries (FUNAI in Brazil, ANT in Colombia, INEI in Peru).
SOC & soils: SoilGrids 250 m (ISRIC); national soil maps (EMBRAPA SiBCS). Plot-based cores remain the gold standard for any VCS-accepted SOC accounting.
Fire: MODIS active fires (MCD14A1), VIIRS 375 m active fires; INPE BD Queimadas; Global Fire Atlas.
HWP (rarely required, but for IFM): national wood-product industry stats (IBÁ in Brazil), IPCC HWP defaults.

2.5 Schema design takeaways

Treat carbon pool as a first-class enum with mandatory / optional-conditional / excluded per methodology.
Treat activity data and emission factor as separate tables joined on stratum + year — never collapse into a single “deforestation t CO₂e” field. Methodologies disagree on which side is jurisdictional.
Make the baseline-source field explicit: historical-projected (VM0007/VM0015), jurisdictionally-allocated (VM0048), dynamic-control-matched (VM0047), community-PRA (Plan Vivo), national-NFMS (ART TREES). These are not substitutable.
Store uncertainty per pool and propagation method so deductions are computed transparently — every methodology audits this.
Capture non-CO₂ emissions inputs (fertilizer N, biomass burning area, fuel use) separately — Gold Standard and several Verra modules require these even when the headline activity is removals.
Buffer pool, leakage factor, and uncertainty deduction should be three separate columns on the issuance — collapsing them is a common cause of double-counting bugs in custom models.