ESA title


  • ACTIVITYDemonstration Project
  • STATUSOngoing
  • THEMATIC AREAFood & Agriculture

Objectives of the service

ProvGRASS_DP objectives

ProvGrass is positioned as a platform-as-a-service offering the first full grass system analysis on the market. The platform helps industry to positively influence management practices to optimise grass cover, resulting in higher quality milk production at better margins. The intention is to combine key information streams: precision yield measurement, sward composition mapping, and biodiversity analysis. This represents a huge leap forward in information-rich grassland management for more profitable farming. 

ProvGrass is designed to be readily deployable at scale with an automated pipeline accessible through published APIs or via a dashboard. It is architected so that its core grass performance data can be augmented with further external data sets such as milk supply or weather information to drive even deeper predictive insights. 

Grass is a notoriously difficult crop to measure over large areas. However, Proveye has developed technology to provide unprecedented knowledge on the status of the grass platform. It will generate multi-temporal maps of grass performance to enable customers to provide products for end-user (e.g., farmers or advisers) grass management. This enables advisory support and interventions based on a full and rich digital view of grassland enabling both historical and predictive insights. 

Users and their needs


Built for firms in the dairy and beef sector, ProvGrass is positioned as the world’s most accurate and comprehensive remote grassland management platform. Grass is the most important agricultural crop in the world, occupying about 77% of agricultural land. The Proveye team has engaged with a variety of potential B2B customers that are looking to either create or significantly enhance an existing advisory service for grassland management. These include:

  • Seed and fertiliser companies

  • Farm management providers

  • Agronomists

  • Dairy producers

  • Beef producers

Customer Needs

Rapidly increasing pressure on our environment and agricultural land means farming practices must now be based on certain, verifiable data to inform sustainable and profitable decision-making. Dependable metrics are essential to protect our environment and secure our future ability to produce food.

ProvGrass allows our target customers to optimise grass use efficiency to improve the quality and profitability of milk production in an increasingly volatile market. They require clear, verifiable data on the change in grass performance to manage feed and input costs as well as prepare for sustainability legislation, such as Scope 3. They also wish to build stronger relationships with their supply base by helping farmers to become more efficient, sustainable, and profitable. Our customers want to sell inputs, services and sustainable solutions, with a value proposition to farmers of increasing profits by optimising grass quality and utilisation. Ultimately, ProvGrass solves for these needs and thus improves the farmer’s bottom line.

Service/ system concept

ProvGrass is a platform-as-a-service for grassland management which provides:

  1. remote mapping and measurement of grass performance including world-leading accuracy in grass yield measurement which maps kg of DM haˉ¹ across farms and regions, and sward composition which can show clover cover, leaf by leaf across the whole farm. 

  2. The capability to monitor a range of biodiversity indicators, which are essential for companies across the food chain who need to measure their Scope 3 impact.

This unique combination of insights to productivity and sustainability remotely measured and monitored from a single platform unlocks huge potential to produce more food with optimised resource usage.

ProvGRASS_DP service concept

ProvGrass employs breakthrough advances in photogrammetry offering image correction algorithms to accurately measure changes in vegetation over time in complex agricultural landscapes. 

ProvGrass also leverages advances in big data and deep learning. The platform’s use of supervised learning opens up the power of artificial neural network architectures allowing its intelligent grassland models to learn, adapt and become even more accurate as more data is provided.

Space Added Value

ProvGrass uses Earth Observation and Satellite Navigation space assets to derive high spatial and temporal resolution data about grass sward composition and quantity. ProvGrass will also allow fusion of UAV and satellite imagery to allow for leaf level information to be extrapolated over large areas. This is important for B2B customers that service tens to hundreds of thousands of hectares. Satellite navigation is used to ensure sub-pixel level georectification. This is critical at the plot scale when looking at time series data and change detection, as any spatial shift in the image stack will result in significant error in the final product. Multi-platform satellite data from various providers increases the likelihood of cloud free images over target areas. High temporal resolution image stacks are key for a dynamic crop like grass, therefore the <10-day revisit time is a crucial feature of the platform.

Current Status

The platform has just gone through its first testing phase through this Demonstration project with remarkable success. The platform seamlessly integrates Proveye’s core IP in satellite (ProvSAT) and UAV (ProvUAV) image processing to give unprecedented accuracy at any spatial scale and using any form of image sensor or camera. This testing phase has involved a ground validation campaign across a large range of farms in the UK and Ireland, with cut and weigh grass samples as well as plate meter readings used for training and validation of various models. 

The capabilities around sward composition (figure 1) and yield measurement (figure 2) are being tested using both historical and realtime image data to ensure the models see a large range of inter-seasonal trends in grass growth and biodiversity.

Proveye is currently engaged with teacher customers in the dairy and beef sectors to validate the efficacy of the model and its commercial deployment at scale. Initial feedback from customers speaks around the ability of the platform to address some of their reporting requirements with respect to Scope 3 emissions.

ProvGRASS achieved over 90% accuracy at detecting individual clover leaves, weeds, perennial ryegrass and bare soil using its advanced AI computer vision models (figure 1).

Figure 1. Shows UAV based near-field images before (left) and after (right) classification using the sward composition model. Broad leaf class is a combination of herbs such as Chicory and PlantainFigure 2. Yield map (Kg DM ha ˉ¹) of individual paddocks in a dairy farm in Ireland using the ProvGrass platform.

Future Plans

The Proveye team will build on the initial work done with teacher customers to secure full commercial deployment of ProvGrass in key markets. The platform itself will continue development cycles to meet full commercial deployment requirements based on teacher customer feedback, nominally in the areas of API integration and grass model maturity. With rich grass data as a base, the Proveye team will seek to exploit this by adding a rich set of biodiversity indicators to assist our customers in meeting Scope 3 requirements. 

A further area of exploitation for the platform is its ability to digitally monitor, report and verify carbon sequestration. With grassland cover > 40% of terrestrial land, the opportunities to use accurate data to independently report on biomass change and subsequent changes in soil carbon stock opens up huge potential for the ProvGrass platform. 

Prime Contractor(s)

Status Date

Updated: 27 November 2023