AI identifies crops from space with 90% accuracy

  • Agrimetrics launches CropLens AI, a proprietary algorithm that identifies crop types from space. 
  • Identifications occur earlier in the season and with higher accuracy than previously possible.
  • Commodity markets, supply chain forecasting, and farm input optimisation all stand to benefit.

 Agrimetrics, the Agrifood Data Marketplace, has launched CropLens AI, an advanced machine learning algorithm that identifies crops from satellite-derived cloud-penetrating radar. This capability is a critical enabler for a variety of solutions, including disease and pest prediction, optimising nitrogen applications, irrigation, and yield prediction.

Artificial Intelligence (AI) has been used to classify crops from space before. However, Agrimetrics CropLens AI is differentiated by:

  1. An industry-leading max accuracy of over 90%, achieved in the one to two months prior to harvest.
  2. High levels of accuracy earlier in the season, e.g. winter wheat can be predicted with 65% accuracy as early as October.
  3. Improved usability and actionability through pre-linking to billions of relevant agricultural datapoints on the Agrifood Data Marketplace.
  4. The use of cloud penetrating radar data, meaning the classifications are insensitive to cloud cover.

Agrimetrics CropLens AI identifies 5 crop types – winter wheat, winter barley, oilseed rape (OSR), grass, and other – in UK fields; however, there are plans to expand this to include a wider range of crops and geographies. Historic data are available from 2017 and in-season predictions available now…Read more