SPATIAL – Soybean Price forecAsting based on saTellite-derIved services and Artificial intelligence

The main objective of SPATIAL is to provide a proof-of-concept (PoC) prototype for forecasting soybean futures contracts price moves using Artificial Intelligence models based on financial & macroeconomic features and Earth Observation products. SPATIAL is realizing two distinct Machine Learning (ML) models, one for soybean crop yield forecasting and one for prediction of soybeans futures contracts price moves, to demonstrate the feasibility of the method, the benefits of integrating Copernicus EO products and to showcase the potential of such approach. Predictability of soybeans futures contract price moves  is particularly important to agricultural organizations, food companies or even to traders.

The SPATIAL solution builds upon a) the expertise of the prime contractor, HYPERTECH S.A. (www.hypertech.gr), in financial assets price forecasting through machine learning and predictive analytics models for financial asset prices prediction based on traditional and alternative data sources along with its multi-year expertise on financial markets dynamics and deep knowledge on the key factors affecting commodities prices b) the expertise on the development and deployment of Space-based applications of NOA (www.noa.gr) for estimating soybeans crop yields and production.