We are currently living in an era of easy access to information, studies have repeatedly used satellite data to successfully track crop phenology at various scales, ranging from sub-field to country estimations. Creating simple crop monitoring and forecast models that integrate satellite, weather, and field data with statistical machine learning techniques like random forest and neural networks will help predict crop development and stage in near real-time.

To accomplish this aim, we are investigating the impact of high temporal and spatial resolution products in collaboration with Planet Labs.
Spoiler alert: for almost any phenological stage, this new product will assist in achieving outstanding high levels of accuracy.

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Impact of High-Cadence Earth Observation in Maize Crop Phenology Classification: https://www.mdpi.com/2072-4292/14/3/469/htm