Farming is often criticized for its environmental credentials – it consumes over 70% of the entire worlds freshwater supply, over 30% of the Earth’s land is taken up for crops - however – agriculture feeds over 7 billion people and employs over 30% of the entire global workforce – it is essential to human life.
Fusing together images from different satellites and using supervised machine learning models enables highly precise information to be obtained about crops. By building an accurate picture of crops, farm by farm, is possible to know exactly what is being grown, across an entire region and plan accordingly.
Predicting crops and crop yields has been tried for centuries. A hundred years ago regression models were used. Now satellite data, combined with machine learning, is used to predict crops. It's only very recently becoming accurate.
Commodities: Crop Predictions Challenges The challenges of predicting crop yields are significant, as outlined in the previous article. Traditionally these challeng...