EOSDA Gets First Ready-to-Use Images From The EOS SAT-1 Satellite
EOS SAT-1, the initial small optical satellite of the first agri-focused satellite constellation launched by EOS Data Analytics, sent its first ready-to-use images of the Earth.
Agrinova Grows By Offering Satellite Data Analytics
Agricultural consulting Agrinova Group has been using EOSDA Crop Monitoring for over two years now, pioneering remote sensing services in the European Union and Eastern Europe.
Lidar vs. Radar: Differences & Uses To Pick The Right One
Lidar targets objects with pinpoint accuracy, while radar delivers wide, all-weather coverage. But it's not so much lidar vs. radar in real-world applications as picking the right tool for the job.
Making Gas Mining Safer For Agriculture In Australia
This story of impact explores the impacts of coal seam gas mining in Queensland, Australia, through the lens of a local farmer witnessing soil subsidence and increased moisture in her fields.
Variable Rate Seeding: Technology Application & Benefits
EOSDA Crop Monitoring streamlines precision agriculture with Variable Rate Seeding maps. Methods of using vegetation indices for applying variable rate seeding are discussed in this simple guide.
Agricultural Water Management With Sustainable Methods
Agriculture accounts for 70% of global freshwater use, highlighting the need to improve on-farm water management. Let’s explore smart approaches aimed at increasing agricultural water use efficiency.
EOS Data Analytics Partners With Susanne Schödel GmbH
EOS Data Analytics and Susanne Schödel GmbH announce a strategic partnership to deliver AI-based satellite imagery analytics and improve crop monitoring and environmental conservation in DACH market.
Evapotranspiration Process And Methods Of Measuring
Evapotranspiration is the process of water vapor loss from the soil and plant surfaces. Farmers who are aware of the ET effects on crops are in a better position to increase their farm productivity.
EOSDA Aids Higher Crop Yields With Productivity Maps
Oleksandr Dzhevaga & Aleksey Kryvobok, EOS Data Analytics, discuss models for custom crop productivity mapping, developed as a result of in-house collaboration between data and soil scientists.