Integrated system approach becomes key pillar for sustainable intensification of agri-food systems while ensuring ecological functions under changing climate, diet and demography. The digitization of the agroecosystems become most essential entry point for any sustainable developmental entities whether it is plant genetics for breeding better varieties, crop diversification and intensification, efficient use of farm inputs, agronomic practices, stable economic return, to ecosystem services management. The functional production systems become more important than single commodity production systems. Recent advances in Earth Observation System (EOS), Open-Access (AO), Artificial Intelligence (AI), Machine Learning (ML), Information, and Communication Technologies (ICTs), Cloud Computing Platforms (CCP) along with smartphone-enabled Citizen Science (CS) increasingly make Big-Data analytics much smarter, interoperable and much useful than ever before, and create valuable baseline information for decision making. This has opened tremendous opportunities to address the knowledge gaps at multiple levels (e.g., data, yield, ecology, economy, resilience) for demand-driven ecological interventions across the scale (e.g., space, time and package). Ongoing efforts in big-data driven digital augmentation aim at quantifying functional production dynamics and drivers to target site-specific sustainable developmental interventions and scaling the ecological intensification such as intensification of pulses in cereal-based systems (rice fallows), adoption of conservation agriculture, bridging the yield gaps, geo-localization of the research and impact reporting. Here we present some of the ongoing efforts in EOS Big Data for digital augmentation for accelerating agroecological intensification in different agroecologies and regions in the drylands.