For those navigating the ever-changing world of carbon credits, understanding the mechanisms that underpin their integrity is paramount. In the agricultural sector, where the enormous potential of carbon dioxide equivalent (CO₂e) sequestration is increasingly being recognised, utilised and rewarded, a robust system of verification is crucial. This is where dMRV comes into play.

The acronym dMRV stands for digital measurement, reporting and verification. These mechanisms enable carbon removals to be quantified and validated, in turn producing carbon credits and supply chain insetting solutions.

At Agreena, dMRV is at the heart of our Verra-registered AgreenaCarbon programme. Designed, built and maintained in-house, our bespoke dMRV technology is the backbone that allows us to confidently verify the adoption of regenerative farming practices on specific fields throughout Europe, across entire growing seasons. This best-in-class verification process ensures the environmental impact claimed by our farmers is accurate and auditable, fostering trust and credibility in the carbon credits they generate.

So, how does dMRV work in practice? For Agreena, it involves a powerful combination of cutting-edge technology and on-the-ground expertise. Two of the primary tools in our dMRV toolkit are remote sensing and field boundary detection.

Imagine being able to observe vast tracts of farmland, tracking changes and identifying specific activities without ever setting foot in the field. This is the essence of remote sensing – capturing measurements of a location from a distance. While drones and cameras can play a role, our dMRV approach at Agreena predominantly harnesses the power of satellites.

To gain a comprehensive understanding of the agricultural landscape within our programme, we utilise two distinct types of satellite technology: optical and radar.

Optical satellites: Like a camera in the sky

Think of optical satellites as highly sophisticated cameras orbiting the Earth. They capture images by detecting the sunlight that reflects off the Earth's surface. This reflected light contains a wealth of information about what's happening below.

One crucial metric derived from optical satellite data is the Normalised difference vegetation index (NDVI). This index cleverly uses the red and near-infrared bands of the electromagnetic spectrum to gauge the health and density of vegetation. Healthy plants have a unique spectral signature; they reflect more near-infrared light and absorb more red light. Consequently, when crops are actively growing, the NDVI value increases. After harvest, when vegetation is absent, the NDVI drops significantly. By analysing NDVI trends over time, we can remotely verify the presence and growth cycles of crops, a key indicator of certain regenerative practices like cover cropping.

Radar Satellites: Peering Through the Clouds

While optical satellites rely on sunlight and clear skies, radar satellites offer a different perspective. They actively send out microwave signals towards the Earth's surface and then measure the reflected signals. This technology is particularly sensitive to surface roughness and moisture content, making it an invaluable tool for detecting changes in soil structure and identifying tillage type.

Crucially, radar technology, specifically Synthetic aperture radar (SAR), can acquire data regardless of weather conditions, including cloud cover and darkness. This ability to consistently gather information throughout the season provides an extra layer of insight into on-the-ground activities, complementing the data gathered by optical satellites.

By intelligently fusing the data streams from both optical and radar satellites, we build a richer and more nuanced understanding of the activities taking place in our farmers' fields. This wealth of information then feeds into our advanced machine-learning models, which are trained to accurately identify and verify specific regenerative agricultural practices.

Before we can even begin to monitor farming practices, we need to accurately define the boundaries of each field participating in the AgreenaCarbon programme. This process, known as field boundary detection, is a critical first step in ensuring the precision of our carbon calculations.

At Agreena, our field boundary detection follows a structured four-step process:

1. Farmer input: Our AgreenaCarbon farmers provide the precise latitude and longitude of the central point, or centroid, of each of their fields. This initial information acts as an anchor point for our analysis.

2. Satellite tile matching: This centroid is automatically linked to the corresponding Sentinel-2 tile, a 110km² section of the Earth's surface captured by the European Space Agency's optical satellite constellation. This ensures we are focusing our analysis on the correct geographical area.

3. AI-powered inference: Our in-house, expertly trained field boundary detection model then analyses the selected Sentinel-2 tile over the relevant date range. This sophisticated model uses image processing techniques to identify the unique visual signatures of field boundaries, effectively delineating the specific area of interest.

4. Land use verification: Finally, each identified field is integrated into our pipeline for thorough land use checks. We cross-reference the satellite-derived boundaries with official government ordinance survey maps to confirm that the land is indeed classified as agricultural land. This crucial step adds another layer of validation to the process.

This meticulous field boundary detection process ensures that our subsequent monitoring and verification efforts are focused on the correct agricultural areas, forming a solid foundation for accurate carbon accounting.

Our market-leading dMRV technology provides precise, real-time, and continuous monitoring of the agricultural land within our AgreenaCarbon programme. This constant vigilance, powered by satellite data and sophisticated analysis, underpins the credibility and integrity of the CO₂e outcomes delivered by our dedicated farmers.

By combining the broad overview of satellite remote sensing with the granular detail of field boundary detection and, importantly, physical farm visits for visual inspection, Agreena offers a multi-layered and robust verification system. This comprehensive approach ensures that the carbon credits generated through our programme are trustworthy and accurately reflect the positive environmental impact of regenerative agriculture.

For professionals in the carbon credit market, dMRV is a crucial component of the fundamental principles of transparency and accountability that drive a credible and impactful system. At Agreena, we believe that our commitment to rigorous dMRV is essential for building a future where agricultural soil carbon credits are a trusted and effective tool in the fight against climate change.

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