Case Study: a customer from Kyrgyzstan achieves sugar beet crop mapping and field boundary detection with EOS

Customer From Kyrgyzstan maps sugar beet fields in Kyrgyzstan with EOS using 4 crop classes

A customer from Kyrgyzstan, a sugar beet producer, faced challenges in optimizing production and logistics due to the unique topography of their fields situated in valleys. They engaged vendor EOS to utilize a custom neural network model for crop classification and field boundary detection to gain a clearer understanding of field sizes and locations.

EOS implemented a solution using a convolutional LSTM neural network trained on satellite imagery and ground data. The results provided the client with a detailed map identifying sugar beet, corn, alfalfa, and other crops, enabling them to calculate actual acreage, adjust cultivation and logistics, and improve yield planning and assessment for their sugar production business.