Rezatec applies its geospatial data techniques to extract specific spectral indices across the growth cycle to create a signature that identifies the crop, using both optical and radar satellite data sources. By applying its in-house machine learning algorithms to these indices, Rezatec can distinguish potato from other crop types with up to 95% accuracy.
Additionally, through active remote sensing monitoring, Rezatec can also assess variables of crop performance, e.g. health, against the crop model through the growing season, and, using its data science techniques provide growers with critical information to take corrective action and ultimately increase crop yields.
Dr Jim Dimmock, Resource Management Scientist at AHDB summarised: “It is evident from our collaboration with Rezatec that the application of satellite data for mapping crop extent is of great value and compared to more traditional methods, we were impressed by the ability to scale across large areas with high levels of accuracy.”
Dr Andrew Carrel, Chief Technology Officer at Rezatec commented: “Rezatec’s agriculture management services are very versatile, ranging from identifying crops at a field, and even sub-field level, and monitoring crop performance, up to macro-level analytics to support commodity crop trading for multiple end-users including Government and traders.”
Rezatec provides its agricultural management services around the world to a wide range of agricultural end-users from sugar cane and wheat farmers in Mexico to dairy farmers in the UK.