What information can be extracted from EO data?
Outlier and anomaly detection provides information whether a crop field is deviating from the norm due to different practices, climatic conditions, pests, delayed sowing or drought.
We have integrated machine learning algorithms to identify planted crops for subsidies controls and IAC Systems.
We provide smallholder support by creating transparency of the land through crop and land use classification based on machine learning and EO data analysis.
Finance & insurance applications
In the finance and insurance sector up-to-date satellite informations are a valuable source of independent monitoring data. They can be used to document activities and evaluate cropland.
Mobile apps can be used for crop scouting or crop health analysis in the field.
Due to our efficient system the data amounts transferred to a mobile device are small and even in areas with limited bandwith are still performing well.