The Smallholder Blind Spot in Carbon Finance Data

Smallholder farmers sit at the heart of global reforestation and agroforestry efforts. Across Africa, millions of small plots collectively contribute significant carbon sequestration, biodiversity protection, and livelihood support. Yet despite this importance, smallholder landscapes remain one of the least accurately measured components of the carbon finance ecosystem.

This gap is not intentional, nor is it a failure of satellite technology. Instead, it reflects a structural blind spot in how global monitoring systems have been designed, trained, and deployed.

Most carbon monitoring systems rely heavily on satellite-derived datasets. These tools are essential for observing change at scale and perform well across large, continuous forests. However, when applied to fragmented smallholder landscapes, they often struggle to accurately detect tree height, species composition, rotational harvesting, and plot-level management practices.

In smallholder contexts, trees are planted in dense, mixed-use systems, often intercropped with food crops and managed on short harvest cycles. Canopies are irregular, plots are small, and land-use boundaries are complex. Many global datasets are optimized to detect forest cover and deforestation against a fixed baseline, not the dynamic reality of managed smallholder systems. As a result, satellite models may underestimate biomass, misclassify planted trees as general vegetation or rangeland, or fail to register harvesting events that do not meet strict deforestation definitions.

The consequence is material. When tree stock and growth are underestimated, carbon projects appear to underperform. Reported sequestration falls below reality, credibility is questioned, and smallholder farmers receive lower payouts or are excluded entirely. Over time, this erodes trust in carbon finance and weakens its ability to deliver equitable climate outcomes.

Addressing this blind spot requires reframing the problem. The issue is not whether satellites are useful, but whether they have been sufficiently trained on smallholder realities. High-resolution satellite products, including canopy height and land-use classification datasets, are only as accurate as the data used to train them.

This is where ground truth becomes essential.

Systematic, high-quality ground data collected from smallholder plots can capture the parameters that satellites struggle to resolve on their own: tree height distributions, canopy structure, species mix, planting density, and management cycles. When this ground data is used to inform and strengthen satellite-based models, accuracy improves precisely in the landscapes where current systems fall short.

Field-based sampling does not replace satellite monitoring. Instead, it acts as connective tissue, allowing scalable remote sensing systems to better reflect reality on the ground. Each additional smallholder plot sampled improves model performance not only locally, but across regions with similar ecological and farming characteristics. Over time, this creates a compounding return on investment in data infrastructure.

Importantly, this challenge should not be framed as criticism of existing datasets or institutions. Many global platforms are transparent about their design scope, baseline definitions, and intended use cases. The limitation lies in the absence of sufficient smallholder-specific training data, not in analytical rigor.

Closing the smallholder data gap is therefore both a technical and an equity issue. Without accurate measurement, smallholder farmers remain invisible in climate finance systems despite doing meaningful climate work. With better data, carbon markets can become more inclusive, more trustworthy, and more aligned with real-world outcomes.

Solving this problem requires collaboration. Researchers, carbon developers, technology providers, farmer organizations, and funders all have a role to play. Strategic investment in ground-truth data collection, open model improvement, and shared learning can unlock disproportionate gains in MRV integrity.

When smallholders are properly measured, they are properly valued. And when they are valued, carbon finance can begin to deliver on its promise not just at scale, but with fairness.