To create our insights, we utilize a series of state of the art technologies. The core of CropOM's solution based on satellite data, image processing, and time series analysis. We use the data of three satellite families (Sentinel-1, Sentinel-2, and Sentinel-3 ) of the European Space Agency's Copernicus Programme. Synthetic Aperture Radar and Optical Remote Sensing (multispectral) data are combined and further enhanced with meteorological data to create excellent data sets for analyzing crop health, phenological state, and agro-hydrological anomalies.
CropOM uses time-series statistics and multispectral analysis to detect underperforming areas during the growing season, helping our end users, farmers, and agronomists, to know where to find the problem, even in large fields. The cause of such a decline in crop development is some times quite evident, for example, in the case of agro-hydrological anomalies as drought or standing water, that we can detect it from space and provide exact answers. Other times the cause is obscure enough that it needs a field survey to be sure about the problem and the ensuing solution. In both cases, CropOM provides excellent stats and maps with quantified data highlighting the problematic areas.
For advanced insights such as regional statistics, water balance, and yield forecast, we utilize scientifically proven deep learning algorithm. Our algorithm constantly improves as the data volume, which it uses continuously growing over time.
To support Variable Rate Technology, we provide parametrized prescription maps for the agricultural machinery in standard ISO-XML format.
We provide CropOM's data through a standard RESTful API, which we created with the specific needs of web-based Farm Management software and ERP systems in mind, hence the seamless integration.