Scientists at Tomsk State University (TSU) have developed a prototype of a digital field for the implementation of "smart" agriculture in Altai, which will increase yields, improve crop quality and reduce economic risks associated with crop failure. This model combines data from various sources, including remote sensing of the Earth, drones, meteorological sensors and field research results.
The project began with a field expedition to Cherga, where aerial photography was carried out using drones, and soil samples were taken. This data allowed us to create a digital terrain model for the specific conditions of Altai, where the terrain is heavily "dissected", which makes standard developments for flat areas unsuitable.
In the future, the prototype will be refined to include additional data, such as slope steepness maps, geochemical migration of elements, and nutrient distribution. The result will be an analytical geoinformation system using machine learning methods that will allow agronomists and agricultural producers to assess the condition of land, predict results, and make informed decisions on agronomic technologies, such as optimizing fertilizers and selecting crops for planting.
This system will be available through a ge портал, providing convenient access to data and decision support in agronomic practice.
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