Introduction: Leveraging remote sensing for Practice Verification

Identify discrepancies between farmer-reported with satellite monitoring.

What is Program Data Review (PDR)? 

Verifying practices happening on the field is critical for generating credible, high integrity carbon outcomes. At Regrow, PDR refers to the use of satellite monitoring for practice verification. Using remote sensing data for practice verification is a good choice for large programs that are looking for objective field practice data at scale, where other methods of verifying practices are not a reasonable choice for the size of the program.

This technology identifies data discrepancies between remotely sensed and farmer reported data for the reporting year (e.g., the harvest to harvest cycle where a practice change is implemented).

Importance of PDR in MRV programs

Any company using the MRV/API to make field-level claims about practice changes leading to reductions or removals—whether for inventory accounting or credit generation—should ideally incorporate PDR.

PDR ensures program integrity by identifying when growers may unintentionally or intentionally misrepresent practice adoption in MRV. It allows customers to focus on higher-risk producers using remote sensing, reducing reliance on random spot-checks or on-field audits. Importantly, PDR can be leveraged proactively, even outside of formal audits, to enhance confidence in program outcomes and improve operational efficiency.

Carbon protocols typically mandate internal processes for verifying farmer-reported data. Remote sensing, as utilised in PDR, is widely recognized as a credible and scalable verification method. Other approaches—such as spot checks, on-field audits, or detailed grower call logs—are often resource-intensive and less scalable, making PDR a key tool for programs seeking both efficiency and reliability.

In addition to meeting current-year audit requirements, many programs involve a five-year “true-up” process, especially when models like DNDC are used. Without robust verification methods like PDR, discrepancies between modeled outcomes and ground-truth samples during a true-up can lead to significant adjustments, potentially undermining program credibility and outcomes. 

Regrow API Customers can leverage outputs from Monitor API directly and build their logic to flag fields and practices. Regrow MRV Customers will be provided with a report that automatically flag fields and practices.  

When/where is Monitor remote sensing data applicable for verifying practices?

Limitations of PDR

While remote sensing data is an efficient way to get objective field-practice monitoring for a large number of fields, there are some field scenarios where it’s not a reliable tool for verifying practice adoption:

1. Weather and cloud cover can reduce the reliability of remote sensing data
   Remote-sensing data used by Monitor leverages observations and data collection from satellites. Satellite imagery cannot be used to interpret field practices during periods of cloud cover or when there is consistent snow cover on the ground. Monitor reports a confidence value with all practices that factors in the availability of interpretable imagery from the satellites. A practice will have a low confidence score when there’s low-quality imagery for the field, or will report no data for the practice.

2. Monitor become less reliable on fields smaller than 1 acre. Monitor leverages satellite imagery at 30m resolution to interpret field practices. On small fields, there are not enough 30m observations to make meaningful practice determinations.

3. Not all intervention practices can be detected using remote sensing. Many satellites typically revisit fields between every 2-7 days. This means that a field may only have 4-10 observations per month. The odds of capturing point-in-time events such as fertilizer or irrigation events applications are low. Remote sensing is much better suited to detect cropping and soil management practices. Additionally, satellite resolution is not sufficient to detect practices such as intercropping, buffer strips or interseeding.

Alternative methods to verifying practices

For fields and practices where remote sensing is not a reliable option for practice verification, we recommend leveraging one of the following alternative methods for verifying intervention practices:

• Site visits: Project developers or agronomist can visit farms to observe and document practices throughout the season.

• Farmer-evidence: Farmers can submit evidence of practice adoption, such as receipts of fertilizers or cover crop seed, images/videos of the field, or tractor/machinery logs.

• Farmer attestations: Direct farmer reports, interviews or signed attestations of practice adoption. Note: typically auditors want to see this in conjunction with another form of proof.

• AgCensus/government published data: Data backed by governments or academic institutions can be used to support the farmer attestations, by corroborating regional practice norms (ex: regional practice for amount of fertilizer applied on a corn field).

• Agronomist review: An independent agronomist can review practices reported by a farmer, and verify that the practice is regionally common, or makes sense for the particular farm.

Considerations for protocol compliance & carbon credit audits

• Document decisions as they are made

  • For example: Auditors want to understand why a conflict was raised and how it was resolved. Keeping a log of decisions will increase transparency and provide justification.

• Utilize remote sensing in conjunction with other methods, particularly when there is a conflict

  • Box 1 of VM0042 v2.1 outlines industry best practices for data sources. See also Section 6.1 Agricultural Management Data Collection of CAR SEP v1.1.

• It’s important to note the distinction between practice verification and long-term permanence monitoring. Permanence monitoring focuses on long-term oversight of fields to ensure claimed soil organic carbon (SOC) removals remain intact after the field is no longer enrolled in an active program. This involves identifying whether practices continue or if a reversal event occurs, requiring adjustments to previously credited or claimed outcomes. In contrast, PDR is concerned with the current project year, helping to determine whether high-quality claims can be made for ongoing activities.