Agriculture

Build your own agricultural land analytics using a flexible set of functional capabilities from EOS.com

Case Studies

The studies below showcase the results obtained with the help of EOS technologies. Review them to find the solution for your needs. Request a demo to see how it works. If you can’t find what you need, contact us and we’ll assist you!

Agricultural lands can be analysed both for individual needs and to build complex analytical systems based on an analysis of extensive historical data sets from our partners.

Classification of crops in a group of fields. For automatic classification of crops in fields we use algorithms based on neural networks.

This kind of automatic classification can be developed for large expanses of fields using free data from the Sentinel 2 satellites.

On a national scale the classification error is no greater than 20%.

This functionality can be applied for global classification of crops growing within a region and for analysing areas under various crops to plan logistical operations.

For the purposes of global monitoring, EOS.com offers a wide functionality providing the opportunity to build integrated systems based on an analysis of:

  • comparative graphs of vegetation within a single year;
  • comparative graphs of vegetation for crops in different years;
  • graphs comparing vegetation with the same crops in the same region;
  • yield forecasts by crop group;
  • detection and measurement of areas affected by erosion.

Within a single field you can monitor the tiniest deviations from crop growth norms for timely intervention in the growing process.

In addition, EOS.com’s technologies can be used for early forecasting of crop yields on the basis of our own algorithms and unique software solutions.

For the purposes of global monitoring EOS.com offers a wide functionality providing the opportunity to build integrated systems based on an analysis of:

  • comparative graphs of vegetation within a single year
  • comparative graphs of vegetation for crops in different years
  • graphs comparing vegetation with the same crops in the same region
  • yield forecasts by crop group
  • detection and measurement of areas affected by erosion

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