Digital Soil Mapping for a Changing Climate

Reading the land from space

Soil is one of agriculture’s most strategic yet under-monitored resources. Across the UK, Europe and beyond, decades of intensive cultivation, extreme weather and tightening margins have put increasing pressure on the resource every farm depends on – and that pressure is now compounded by tightening regulation and sustainability reporting requirements, as governments and supply chains alike are asked to evidence soil condition rather than assume it. Meeting that scrutiny starts with understanding soil at a level of detail that manual sampling alone cannot deliver quickly, consistently or affordably enough – and that is where satellite Earth Observation comes in.

Application: What is digital soil mapping?

Digital Soil Mapping (DSM) is a method for creating detailed, spatially continuous maps of soil properties using statistical and machine learning models, rather than relying solely on traditional manual surveying. Instead of a handful of point samples taken across a field or a region, DSM combines whatever soil data already exists with environmental variables – terrain, land cover, climate and, increasingly, satellite imagery – to predict soil properties everywhere in between.

The result is a map that is continuous, repeatable, and can be refreshed as new data comes in, rather than a static snapshot that is out of date at the moment it is produced. Crucially, DSM does not replace physical soil sampling – it makes it more effective, by revealing spatial variability upfront so that sampling can be targeted precisely where it adds the most value for validation and decision-making.

What Digital Soil Mapping delivers

Digital Soil Mapping combines satellite image analysis, georeferenced field sampling and laboratory chemical-physical analysis with predictive modelling to build a detailed digital picture of soil across entire fields. Rather than relying solely on individual soil samples, it:

• produces high-resolution soil variability maps (with an operational resolution of 10-30 meters)
• predicts key soil properties such as soil organic carbon, texture, pH, nitrogen, phosphorus and potassium, cation exchange capacity (which measures a soil’s ability to hold and trade positively charged nutrient ions) and electrical conductivity
• generates georeferenced digital maps and field-level reports that support targeted sampling, year-on-year monitoring, and more informed agronomic and supply chain decisions

Together, these outputs form the intelligence layer that satellite Earth Observation makes possible at scale. On real-world deployments, this level of precision has translated into measurable results: up to a 15% reduction in fertiliser use, up to 20% lower water consumption, and up to 35% more effective site-specific interventions, thanks to detailed knowledge of soil variability.

UK expertise: built for what comes next

Abaco Group UK (part of Diagram Group) holds a position in this space that is genuinely hard to replicate: over 30 years of land resource management software developed in Italy, paired with UK delivery experience across DEFRA, the Rural Payments Agency and supply chain clients.

Working with UK crop science organisation Niab, Abaco Group UK developed the Soil Health Scorecard – a digital application that establishes a common baseline to measure and interpret soil health for individual fields or soil zones, and gives farmers tailored, site-specific management advice. Launched with major retail and food supply chain partners, it has been trialled directly within their supply chains, aligning soil monitoring with commercial sustainability commitments rather than leaving it as a standalone research exercise.

At this stage, the Scorecard and Diagram’s Digital Soil Mapping methodology are complementary: the Digital Soil Mapping layer provides the underlying high-resolution soil intelligence, while the Soil Health Scorecard interprets that information to give users a health score, tailored recommendations and management guidance.

Beyond the Scorecard itself, Abaco’s broader work in precision agriculture – an approach we refer to internally as Agriculture 4.0 – shows how satellite and sensor data feed into day-to-day farm management decisions, not just research outputs, from variable-rate prescription maps to irrigation and nutrient planning.

Why satellite data?

Satellite Earth Observation has become central to Digital Soil Mapping for three practical reasons:

• Resolution – modern optical and radar satellites (Sentinel-2 and comparable missions) resolve soil and crop variability within individual fields, supporting the 10—30 metre operational resolution of Diagram’s digital soil maps, not just variability across a wider region.
• Classification of soil variability – satellite image analysis divides each surface into homogeneous zones based on chemical and physical characteristics, giving a clear picture of within-field variability and forming the interpretative basis for planning sampling and interventions more rationally.
• Targeted, representative sampling – using those homogeneous zones as a reference, collection points can be strategically selected to accurately represent soil variability, ensuring reliable data without redundancy and optimising the time and resources spent on physical sampling.

Diagram’s own methodology builds on the same evidence base explored in published Sentinel-2 soil mapping research. A recent peer-reviewed study across two Italian regions – Emilia Romagna and Toscana, together covering over 4,700 hectares – integrated multitemporal Sentinel-2 imagery with soil chemical-physical analysis from nearly 400 sampling points, and found that the resulting models predicted clay content and soil organic carbon with strong accuracy (R² up to 0.88 for clay and 0.71 for organic carbon). See the ScienceDirect study on geospatial soil characterization using multitemporal remote sensing for a public example of the underlying science.

Application in agriculture: from research to supply chain

Soil data is moving from a research input to a compliance and reporting requirement. Climate resilience planning, Measurement, Reporting and Verification (MRV) frameworks and soil carbon as an ESG metric are converging – supply chains and regulators are going to want soil condition evidenced at scale, not measured on a sample of fields.

The wider Diagram Group’s Soil Mapping capability already extends beyond organic carbon into erosion risk indices, water balance estimation and management-zone delineation for variable-rate application, giving supply chains and public bodies a single, satellite-based evidence layer that can support both day-to-day agronomy and formal ESG or regulatory reporting as those requirements tighten.

About Abaco Group UK – Abaco is part of Diagram Group, a leading Italian and European agritech company, formed from the transformation of IBF Servizi and the acquisitions of Agronica, Abaco, Agriconsulting and Netsens. Based in UK, Italy and Malta, Diagram supports farms, food companies, public administrations and financial institutions with satellite-based soil and crop monitoring, precision farming and supply chain traceability solutions. Find out more at https://www.abacogroupuk.com/

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