GeoFarm aim to develop an innovative data-driven agri-food system that will draw on this demand and secure growth. Using the latest advancements in machine learning, artificial intelligence, and big data analytics, they will develop bespoke algorithms that automate real-time analysis of crop spectral signatures from remote sensing technologies – mainly low-resolution satellite imagery. This system will be accessible through a web portal and allow real-time identification of crop types, environmental distress (e.g. hail damage), and predictive yield analysis. This information will help crop producers to improve the quantity, quality, and consistency of their yields, and improved crop availability will help to address both food insecurity and poverty. Government agencies will be able to use yield predictions to plan import/export strategies – avoiding shortages and benefitting from gluts. The new system will be innovative as it will be a cost-effective system based on readily available technologies that is more affordable and timelier than competitor solutions - unmanned aerial vehicles - or current approaches - ground truthing surveys. The new system will initially focus on Maize to develop an accurate and reliable solution. The embedded capability has significant growth potential as it can be scaled to include further types of crop, characteristics, and cover larger land areas.

GeoSpace’s strategic plan is to develop new capabilities that expand their service offerings and help to address food insecurity and poverty in South Africa (SA). This will increase their market share, support expansion into new countries, and ultimately increase turnover and profitability. In 2018, they launched a subsidiary called GeoFarm to respond to increased market demand for data availability and analytics in Agriculture. GeoFarm aim to equip crop producers and organisations with timely information that can inform better decision making and improve crop yield productivity.