Environmental degradation often goes unnoticed until it affects productivity, resilience, and reputation.
Environmental and regenerative risks rarely appear as single events. They develop gradually through changes in land use, soil cover, vegetation health, and ecosystem integrity.
Field audits and periodic surveys struggle to capture these dynamics at scale. Without continuous, land-level intelligence, organizations cannot verify regenerative practices, detect degradation early, or determine whether sustainability investments are delivering real impact.
Measure the presence and continuity of practices such as cover crops, agroforestry, mulch, and reduced tillage directly from satellite imagery.
Monitor land use change, vegetation loss, erosion risk, and ecosystem stress before they translate into long-term exposure.
Follow environmental indicators season after season to understand trends, validate interventions, and support resilient land management strategies.
BAT is advancing regenerative agriculture to reduce ecological risk and strengthen long-term crop resilience across its supply chains. Scaling these efforts requires more than field visits and self-reported practices.
Using Picterra’s GeoAI, BAT monitors environmental and regenerative indicators, including ground cover, erosion risk, and canopy cover, across thousands of farms. This provides earlier feedback on land conditions and supports more informed, long-term decision-making.
Over 90,000 farms
monitored across global supply chains
Tracking key indicators
ncluding erosion risk, canopy cover, and bare soil
Use stable, geolocated polygons to observe environmental indicators across seasons and years.
Detect changes in soil cover, vegetation structure, tree presence, and land use using repeatable, scalable models.
Visualize trends, surface emerging risks, and export results to sustainability, agronomy, or investment workflows to guide action where it matters most.
See how the Picterra Insights Hub brings clarity to regenerative practices and ecosystem health at scale.
