Sustainability and Environment
Software solutions for land managers, rural conservation funds digital and environmental consultants
Need a scalable way for verification of management practices?
With remotely sensed data collection, FluroSense helps you fill in the "data holes" and verify precision data against the country and county-level statistics.
Want to be confident in the reported application data?
Get objective reports of crop type, a record of crop rotation practices, presence of cover crop, its area and biomass and the type of tillage practices that took place in the field.
Have to benchmark operation data against government standards?
Verify field application data against your national standards (USDA/NRCS CMZ, AU State DPI, or NZ MPI) in reviewing management and conservation practices.
Identify crop types and crop rotations to verify management practices at scale
FluroSense crop identification algorithms driven by models trained on remote sensing imagery and agronomic principles help you verify the cropping history of the field and the management practices followed in it including crop type planted in the field, percentage planted area, and the harvest date. You can access the data on a field, farm or region level and select areas for selective ground-truthing.
Verify the cover crop planting areas and tillage practices
FluroSense runs automated crop monitoring algorithms for current and previous crop seasons to estimate the rotation/cover crop type, percentage planted area and its health. Cover crop rotations are crucial for maintaining the nutrient balance of the field and contribute positively to the yields in the coming years. FluroSense modelling tools make it easy for you to estimate this nutrient contribution and monitor adherence to the best practices.
Benchmark nutrient applications data against government suggested levels
Compare operations data with site-specific variable-rate nitrogen recommendation based on scientific bio-physical crop models. The models use farm-specific management information (planting dates, crop types and rotations, and several years of weather data and modelling) to predict the crop biomass status and nutrient requirement at any point in the past two seasons. So when the reporting time comes, you know how your applications rate compares to scientific guidelines.