Choosing the Right Stocking Index for VM0047 Projects

26 February 2026

In our recent VM0047 Performance Benchmarking webinar, where we convened Verra, American Forest Foundation, and MSCI Carbon, one question came up more than any other: How do I choose the right Stocking Index?

Stocking Index (SI) selection shapes data stability, Performance Benchmarks, and VVB confidence. Getting it right ensures the data is working for you, not against you.

Here's what you should know when selecting a Stocking Index for VM0047 projects.

SI Options: Vegetation Indices, Canopy Height, and AGB

• Vegetation indices (NDVI, EVI)
  These indices are ratios of specific reflectance bands seen by a satellite, and can be thought of as a measure of vegetation  "greenness.” They're widely available and have long historical records. But they saturate in dense canopies, are subject  to seasonal variations, and are easily influenced by noise caused by atmospheric effects (clouds, haze, etc.).

• Canopy height
  Canopy height products produce estimates of tree height, which are then used as a proxy for biomass. But height alone misses density because trees can be tall and thin or short and thick. This makes canopy height estimates noisy and less reliable.

• Aboveground biomass (AGB)
  AGB captures both height and density, making it a more accurate proxy for what is most relevant to the VM0047 methodology: carbon. AGB-based indices are more stable over time and correlate directly with carbon stocks.

A Core Trade-Off: Early Detection vs. Long-Term Accuracy

Vegetation indices may detect early-stage change in young plantations. But as forests mature, they become unreliable.

Canopy height is better than greenness metrics but is still not a direct measure of biomass.

AGB is more stable long-term but may be less sensitive in year one or two.

The right choice depends on project stage, forest type, and what you're willing to defend to an auditor.

Baseline Accuracy Matters

A noisy index produces volatile baselines. Volatile and saturation-effect-prone baselines can mean fewer credits in the long term. 

AGB-based indices produce more stable baselines because they're less affected by seasonality and saturation. Stable baselines mean more defensible credits.

Missed the webinar? Watch the recording here.

Have questions about SI selection for your project? Get in touch.