Beyond the Boundary: Hedgerow Biomass Monitoring for Regenerative Agriculture
The global shift towards regenerative agriculture is fundamentally about restoring the health and resilience of our farmlands. While practices like no-till farming and cover cropping are widely discussed, one of the most critical, yet often overlooked, elements of a thriving regenerative system is the hedgerow. These living boundaries are not just fences; they are the needed for a biodiverse and climate-resilient landscape.
Deep Planet is leveraging the power of geospatial AI to provide the accurate, verifiable data needed to manage and restore hedgerows at scale.
Hedgerows and Regeneration
A hedgerow is defined as a continuous boundary line of trees or shrubs over 20m long and less than 5m wide at the base. In the context of regenerative agriculture, hedgerows play multiple essential roles:
Boosting Biodiversity: Hedgerows are considered the largest 'nature reserve' in the agricultural landscape, acting as crucial wildlife corridors that connect fragmented habitats. They provide food, shelter, and breeding sites for a vast range of species, including foraging bats, nesting birds, and the harvest mouse. They are vital habitats for pollinators (bees and butterflies) and pest predators.
Protecting Soil and Water: Hedgerows help reduce erosion from wind and water, keeping valuable topsoil in place. By slowing water flow, they improve infiltration, which helps mitigate flood risk and reduce the loss of sediment, nutrients, and pollutants.
Climate Change Mitigation: Hedgerows sequester carbon in their wood and help build healthier, carbon-rich soils. Their ability to grow faster than some tree systems makes them a relatively swift response to supporting national net-zero carbon goals.
The Challenge of Traditional Monitoring
It is a logistical challenge for farmers, land managers and agricultural businesses to accurately identify and monitor the health, length and width for effective management.
Traditional manual scouting and ground surveys are costly, time-consuming, and only provide snapshots of a large area. This makes it difficult to verify changes over time, track regenerative agricluture projects, or efficiently comply with emerging environmental schemes.
Deep Planet’s AI based Precision Monitoring Solution
Hedgerows and rows of trees (yellow lines) identified in a test site in the UK using Google Earth, PlanetScope and Sentinel-2 image (false colours).Deep Planet solves this challenge by integrating cutting-edge geospatial Artificial Intelligence with high-resolution Earth Observation data. We shift hedgerow monitoring from manual, infrequent snapshots to an automated data-driven system.
High-Resolution Imagery
The ability to detect and characterise hedgerows remotely depends heavily on image resolution. We utilize a mix of powerful satellite data sources to achieve high accuracy:
Very High Resolution (VHR): Images from sources like PlanetScope and Google Earth allow us to identify 100% of hedgerows, providing the detail needed to map their exact length and width.
Time-Series Data: Satellites like Sentinel-2 are critical because they provide multi-temporal images, enabling us to analyse the change in vegetation and health throughout all seasons of the year.
Advanced Remote Sensing: For a complete characterisation, sensors like Lidar and Radar offer the height and volume data necessary for a comprehensive health assessment of the canopy.
2. Automation through Machine Learning
To make this data actionable, we employ different machine learning algorithms to automate the process of hedgerow mapping, drastically increasing efficiency over manual GIS (Geogaphical Information Systems) detection.
Our core technical methods include:
Image Segmentation and Classification: Training AI models to precisely delineate hedgerow boundaries from surrounding crops or land.
Change Detection: Using the time-series data to track new planting, gaps, or changes in canopy health over time.
Deep Learning (U-Net): Utilising advanced deep learning architectures to achieve high accuracy in detecting these thin, linear features across large landscapes.
Cultivating a Data-Driven Future
Regenerative agriculture requires a commitment to monitoring and measurement. By providing an automated, scalable, and verifiable method for hedgerow monitoring, Deep Planet is equipping farmers and agricultural supply chains to:
Quantify Impact: Generate auditable data on biodiversity enhancement and carbon sequestration for sustainability reporting.
Optimise Management: Identify areas needing restoration (gappy hedgerows) or targeted intervention to maximise their ecological function.
Meet Compliance: Easily demonstrate land stewardship and qualify for natural capital and environmental land management schemes.
To discuss how a tailored Geospatial AI pilot can transform your sustainability reporting and help turn this critical asset into an auditable tool for biodiversity and climate action for the upcoming season, contact our team today.