In a rapidly evolving agricultural landscape, technology is driving efficiency and sustainability. AgTech Talk by AgriBusiness Global sat down with Ofer Judovits, Co-founder and CEO of Marvin, to discuss how geospatial and satellite data with artificial intelligence (AI) is revolutionizing the ag industry.
The convergence of space technology and AI is unlocking unprecedented possibilities in agriculture. Judovits highlighted two major technological revolutions unfolding in parallel. The first is the rapid evolution of space technology, driven by advancements in sensor miniaturization and deployment. Companies like SpaceX have made high-resolution, real-time Earth observation data more accessible than ever by drastically lowering the cost of launching microwave-sized sensors. This shift is democratizing spaceborne analytics, opening new applications across climate monitoring, precision agriculture, supply chain intelligence, and risk assessment.
Beyond traditional imagery, satellite technology now includes high-resolution thermal sensors that measure land surface temperatures with precision. This data is invaluable for agriculture, forestry, and climate monitoring. In regions with heavy cloud cover, such as Latin America, LiDAR technology penetrates cloud cover to generate accurate elevation and biomass data. This is crucial for deforestation tracking and land-use planning. Additionally, ground-penetrating radar (GPR) enhances the ability to analyze subsurface soil characteristics, providing key data for carbon sequestration, irrigation management, and infrastructure resilience.
The second revolution is the acceleration of AI adoption, particularly computer vision and deep learning. When combined with advanced sensors and diverse data sources, AI can unlock powerful insights. However, raw data alone has limited value; business logic and contextual intelligence are essential to translate data into actionable strategies. Platforms play a critical role here, transforming raw data into real-world solutions. These platforms enable yield forecasting, risk assessment, vendor screening, and compliance monitoring. By integrating AI-driven analytics with supply chain dynamics, these platforms can predict market fluctuations, optimize resource allocation, and enhance regulatory adherence.
For large enterprises, this means proactive, data-driven decision-making at scale, turning AI into a true competitive advantage. The implications are vast. Farmers can make more informed decisions about crop inputs, reducing waste and increasing yield. Carbon measurement becomes more precise, aiding in sustainability efforts. Supply chain optimization ensures that resources are used efficiently, from farm to table. As these technologies continue to evolve, the agricultural industry stands on the brink of a transformative era, where data and AI drive not just efficiency, but also sustainability and resilience.
