Verra and Gold Standard's New Guidelines on Soil Organic Carbon Estimation Models
This article is an automatically translated version of the original Japanese article. Please refer to the Japanese version for the most accurate information.
This is a newsletter from sustainacraft Inc.
Methodology Updates is a series that covers carbon and biodiversity credit methodologies. This article introduces two guidance documents newly released by Verra and Gold Standard concerning the use of models to estimate Soil Organic Carbon (SOC).
Soil plays a crucial role in absorbing and storing atmospheric carbon, drawing attention as a key component of climate change countermeasures. In the agricultural sector, there is a growing number of ALM (Agricultural Land Management) projects that generate Carbon Credits by transitioning to farming practices that increase Soil Organic Carbon.
However, accurately determining how much carbon has actually increased in the soil requires taking and analyzing soil samples at many locations, and the high cost of this process has been a challenge for scaling projects across wider areas. Therefore, the utilization of modeling techniques to estimate SOC is expected to be a promising approach to reduce these measurement costs and expand projects more efficiently.
From last month to the beginning of this month, Verra and Gold Standard each released new modules related to model-based SOC estimation.
Verra released VT0014 Estimating organic carbon stocks using digital soil mapping, v1.0. This primarily provides guidance for estimating SOC using remote sensing data and machine learning models. We previously introduced this draft in our newsletter, but it has since undergone several revisions after receiving public comments. Below, we will outline the guidance while touching upon the changes from the draft. We will also revisit the differences with VMD0053, which we previously introduced as guidance for biogeochemical models used in ALM methodologies.
Meanwhile, Gold Standard newly announced Soil Organic Carbon Model requirements and Guidelines. This is a significant update, as Gold Standard previously did not have guidance on model-based SOC estimation. While similar in content to VT0014, it is a comprehensive guidance document that also partially includes the scope of VMD0053. Furthermore, a notable point is that it anticipates different, tiered quantification approaches depending on a project's data access and economic circumstances.
These differences in design are expected to significantly influence a Project Developer's decision on which standard to develop their project under. Below, we will introduce the contents of these two guidance documents in more detail.
(All images displayed below are excerpts from the documents introduced.)
Verra's Official Release of VT0014, the DSM Tool
In a previous newsletter, we introduced the draft of a new Digital Soil Mapping (DSM) tool, "CN0137," for which Verra was soliciting public comments.
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Following the public comment period, the official version, VT0014 Estimating organic carbon stocks using digital soil mapping, v1.0, with updated and clarified content, was released on August 26, 2025.
In this chapter, we will provide an overview of this new tool, VT0014, and explain what changes were made from the draft version, along with the rationale behind them.
Overview of VT0014
VT0014 is a tool that provides comprehensive guidance for estimating Soil Organic Carbon (SOC) stocks in agricultural land using a technology called Digital Soil Mapping (DSM) models.
DSM is a technique that combines various spatial data and machine learning models to visualize soil conditions like a map. Specifically, it uses spatially explicit variables as inputs, such as remote sensing data, topographic data, and various climate-related variables. The goal is to map SOC stocks over wide areas at high resolution by training machine learning models with these data and analysis results from actual soil samples.
A major feature of VT0014 is the high degree of flexibility regarding the models and data used. However, to ensure the reliability of the models, it is mandatory to collect new soil samples at the project site at least once every five years to re-verify the model's accuracy.
Differences from VMD0053 (BGC Model)
Verra's methodologies already include guidance for GHG quantification using biogeochemical (BGC) models, known as VMD0053. VMD0053 was introduced in the following newsletter.
While DSM and BGC share the commonality of being able to estimate SOC stocks, their approaches have several differences.